ols_step_both_p(): Error in if (pvals[minp] <= pent) {: argument is of length zero

DrMondesire commented 3 years ago

When loading the included data set and performing _ols_step_bothp(), the "Error in if (pvals[minp] <= pent) {: argument is of length zero" error is generated. Different pent and prem values were also attempted. _ols_step_bothaic() executes without error.

Edit: _ols_step_bothaic() generates an error when using the predict() function. The following code would be at the bottom of the reprex: stepwisePrediction <- predict(stepwiseBothModel$model, test) Error in UseMethod("predict") : no applicable method for 'predict' applied to an object of class "NULL"

library(tidyverse)
library(olsrr)
#> 
#> Attaching package: 'olsrr'
#> The following object is masked from 'package:datasets':
#> 
#>     rivers

# Import data
finance <- read_csv("https://mondesirecis544quiz1.s3.amazonaws.com/finances/2018_Financial_Data.csv")
#> 
#> -- Column specification --------------------------------------------------------
#> cols(
#>   .default = col_double(),
#>   Symbol = col_character(),
#>   Sector = col_character()
#> )
#> i Use `spec()` for the full column specifications.

# Select only the columns for prediction
financeSelect <- select(finance, Revenue, `Operating Income`, `Earnings before Tax`, `Net Income`)

# Remove NAs
cleanedFinances <- na.omit(financeSelect)

# LM: Predict Revenue when given Income and Earning Data
lmModel <- lm(Revenue ~ `Operating Income` + `Earnings before Tax` + `Net Income`, data = cleanedFinances)

# Stepwise Both Directions
stepwiseBothModel <- ols_step_both_p(lmModel)
#> Warning in min(pvals, na.rm = TRUE): no non-missing arguments to min; returning
#> Inf
#> Error in if (pvals[minp] <= pent) {: argument is of length zero
stepwiseBothModel
#> Error in eval(expr, envir, enclos): object 'stepwiseBothModel' not found

aravindhebbali commented 3 years ago

Hi @DrMondesire,

Thanks for sharing a reproducible example. We have recently fixed this issue in the development version. The fix will be available on CRAN next month. In the meanwhile, please install the development version of olsrr from GitHub as a temporary solution.

# Install development version from GitHub
# install.packages("devtools")
devtools::install_github("rsquaredacademy/olsrr")

I have reproduced the example below. Please do let us know if you run into any other issues.

library(olsrr)
library(readr)
library(dplyr)

finance <- read_csv("https://mondesirecis544quiz1.s3.amazonaws.com/finances/2018_Financial_Data.csv")

# Select only the columns for prediction
financeSelect <- select(finance, Revenue, `Operating Income`, `Earnings before Tax`, `Net Income`)

# Remove NAs
cleanedFinances <- na.omit(financeSelect)

# LM: Predict Revenue when given Income and Earning Data
lmModel <- lm(Revenue ~ `Operating Income` + `Earnings before Tax` + `Net Income`, data = cleanedFinances)

# Stepwise Both Directions
stepwiseBothModel <- ols_step_both_p(lmModel)

                                           Stepwise Selection Summary                                            
----------------------------------------------------------------------------------------------------------------
                                  Added/                   Adj.                                                     
Step          Variable           Removed     R-Square    R-Square      C(p)          AIC              RMSE          
----------------------------------------------------------------------------------------------------------------
   1    `Earnings before Tax`    addition       0.428       0.428    107.3960    208780.1023    15695091332.0867    
   2     `Operating Income`      addition       0.436       0.436     45.4310    208719.2069    15577817874.3278    
   3        `Net Income`         addition       0.442       0.442      4.0000    208677.9584    15497686227.1884    
----------------------------------------------------------------------------------------------------------------

aravindhebbali commented 3 years ago

Regarding ols_step_both_aic() generating an error, let me know if this happens in the development version as well. I tried it with the latest development version available on GitHub and am reproducing the results below

library(olsrr)
#> 
#> Attaching package: 'olsrr'
#> The following object is masked from 'package:datasets':
#> 
#>     rivers
library(readr)
library(dplyr)
#> 
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#> 
#>     filter, lag
#> The following objects are masked from 'package:base':
#> 
#>     intersect, setdiff, setequal, union
library(rsample)

# read data
finance <- read_csv("https://mondesirecis544quiz1.s3.amazonaws.com/finances/2018_Financial_Data.csv")
#> 
#> -- Column specification ------------------------------------
#> cols(
#>   .default = col_double(),
#>   Symbol = col_character(),
#>   Sector = col_character()
#> )
#> i Use `spec()` for the full column specifications.

# Select only the columns for prediction
financeSelect <- select(finance, Revenue, `Operating Income`, `Earnings before Tax`, `Net Income`)

# Remove NAs
cleanedFinances <- na.omit(financeSelect)

# split into train and test
set.seed(1353)
data_split <- rsample::initial_split(cleanedFinances)
train_data <- rsample::training(data_split)
test_data  <- rsample::testing(data_split)

# LM: Predict Revenue when given Income and Earning Data
lmModel <- lm(Revenue ~ `Operating Income` + `Earnings before Tax` + `Net Income`, data = train_data)
lmModel
#> 
#> Call:
#> lm(formula = Revenue ~ `Operating Income` + `Earnings before Tax` + 
#>     `Net Income`, data = train_data)
#> 
#> Coefficients:
#>           (Intercept)     `Operating Income`  `Earnings before Tax`  
#>             2.030e+09              1.645e+00              5.807e+00  
#>          `Net Income`  
#>            -2.437e+00

# Stepwise Both Directions
stepwiseBothModel <- ols_step_both_aic(lmModel)

# stepwise summary
stepwiseBothModel
#> 
#> 
#>                                             Stepwise Summary                                             
#> -------------------------------------------------------------------------------------------------------
#> Variable                  Method        AIC            RSS            Sum Sq        R-Sq      Adj. R-Sq 
#> -------------------------------------------------------------------------------------------------------
#> `Earnings before Tax`    addition    157018.025    8.851326e+23    6.604662e+23    0.42732      0.42714 
#> `Operating Income`       addition    156987.778    8.761034e+23    6.694954e+23    0.43316      0.43280 
#> `Net Income`             addition    156974.448    8.718431e+23    6.737557e+23    0.43592      0.43538 
#> -------------------------------------------------------------------------------------------------------

# stepwise model
stepwiseBothModel$model
#> 
#> Call:
#> lm(formula = paste(response, "~", paste(preds, collapse = " + ")), 
#>     data = l)
#> 
#> Coefficients:
#>           (Intercept)  `Earnings before Tax`     `Operating Income`  
#>             2.030e+09              5.807e+00              1.645e+00  
#>          `Net Income`  
#>            -2.437e+00

# predict
stepwisePrediction <- predict(stepwiseBothModel$model, test_data)
stepwisePrediction
#>            1            2            3            4            5            6 
#>  17104768187 -93875794170 396973832540   3564820894  87264581558  29750234601 
#>            7            8            9           10           11           12 
#>    550218192   1832517325  17427446774   4121332625  45694129495  34360854778 
#>           13           14           15           16           17           18 
#>  13941713000  47490730029   5157363319   7248929645  16496489439  16983022847 
#>           19           20           21           22           23           24 
#>   2811847787  14425406968   1696093593  30379799005   2477872130  -3968881015 
#>           25           26           27           28           29           30 
#>  31015328037   3722391379  17292584387   5666477564   3317867838  15316382118 
#>           31           32           33           34           35           36 
#>  12183776046   4336333676  54281714845  38400254575   3514434409   1847175271 
#>           37           38           39           40           41           42 
#>  38304635355   2073309406   4131238108   3301694683  63367398095   2281561773 
#>           43           44           45           46           47           48 
#>   2613745190  24283379780   2857010074  34673083116  16146831132  34531433040 
#>           49           50           51           52           53           54 
#>  14395133299   4489950476   -662114642   5686236342  13733347698   2351740367 
#>           55           56           57           58           59           60 
#>  66506937044   3070293046  13185271103  13597695213   5219057110   3011548185 
#>           61           62           63           64           65           66 
#>   4590067602  22994300572   7995004290  21489616132  13676427480  10391149571 
#>           67           68           69           70           71           72 
#>   5160031026   5157045072   1730084261   3154142061  36520372842  24963577428 
#>           73           74           75           76           77           78 
#>   1709014261  11219132911  18611040192   1968704859   3213355891  14900426133 
#>           79           80           81           82           83           84 
#>   1736372402   5485849721  21458522451   4788321593  12588970731   1883422360 
#>           85           86           87           88           89           90 
#>   3847115444  -1999054830   3439582030   8288151742   5576160752 173182001547 
#>           91           92           93           94           95           96 
#>   6173283024   3141440182   -532427371  10547728602   2698040922   3138485160 
#>           97           98           99          100          101          102 
#>   7338238961   5398356337   4426541340   2307550862  36865879274   8253593631 
#>          103          104          105          106          107          108 
#>   4828279344   1720796866  16643978510   1019695091  22441917646   2623933902 
#>          109          110          111          112          113          114 
#>   3051302542  10031880544    752292257  12729885277   2992764150   4319420021 
#>          115          116          117          118          119          120 
#>   3253364361   9449121572   7104944568   2128118010   5364768531   3246664550 
#>          121          122          123          124          125          126 
#> -35708500134   2483508722   2026476459   4109728872   9501905016  28116054257 
#>          127          128          129          130          131          132 
#>  -6610597156  10616172765   1944615064   2459859662  28488098525  14992189350 
#>          133          134          135          136          137          138 
#>   5002942401  21391289752  14181305716   2173020280  47810649310   1901078536 
#>          139          140          141          142          143          144 
#>   4401762391   1885900127   2609897678   4683802984    351098265   5591486060 
#>          145          146          147          148          149          150 
#>   5093419750  20936595066  15685340603   3874259450  11251618407   -435383500 
#>          151          152          153          154          155          156 
#>  11326879547   1572714571   6043451109   3226172419   8909324721   2851592018 
#>          157          158          159          160          161          162 
#>   2380230904   2799760075   3260828651   2987480608   4257125569   2389395873 
#>          163          164          165          166          167          168 
#>   2184796619   1506064305   1646086189   7644438324  19078413957  62282579594 
#>          169          170          171          172          173          174 
#>   8593219518   1931164651   2365288127    151411628   6385515432    432961475 
#>          175          176          177          178          179          180 
#>   1608478768  10997433374   1088722805   2353785373   2070669025  20038180173 
#>          181          182          183          184          185          186 
#>   2120694893  17527822754   1810634339    484003023   2097895335   4401132350 
#>          187          188          189          190          191          192 
#>   3421056755   2908281447   2905499015  15467655572  11141142574   1092097616 
#>          193          194          195          196          197          198 
#>   5129394694   2227344108   3315946735   1939329176   9080122619   1953088733 
#>          199          200          201          202          203          204 
#>   2477865823  21976690498   3488050722   2517573372   1219016172   3608169713 
#>          205          206          207          208          209          210 
#>   5083867505   7379378888   1648676961   7053227393   4068263197   5093535905 
#>          211          212          213          214          215          216 
#>   3815563800   9596597909   4377107711   3415949028   3368053454   1460403611 
#>          217          218          219          220          221          222 
#>   1161136302   1978255554  15737811026   2335887577   4180496992   8119159258 
#>          223          224          225          226          227          228 
#>  18528253403   4772003392   3399670169   3152350721   1393846773   2087713676 
#>          229          230          231          232          233          234 
#>   3507557456   8702332032   4982489669   4173860245   2597617747   5788349357 
#>          235          236          237          238          239          240 
#>   2937530661   2126493425   6173995387   2303154605   1912957849   8983605351 
#>          241          242          243          244          245          246 
#>   2356317772  12568147153  10460470916   1762776977   2166748985  27042567344 
#>          247          248          249          250          251          252 
#>   2458496412   2898584066   3544068284   1905114070   1817751440   2036067359 
#>          253          254          255          256          257          258 
#>   5180218434   4336355088   6184073542   6666083833   7099165654   1324066092 
#>          259          260          261          262          263          264 
#>   1443170936   2807557477   4636710989   5610476348   1013598586   4029593588 
#>          265          266          267          268          269          270 
#>   9422299463   7969823899 -12363224457   1808962211   1948339270   2534905567 
#>          271          272          273          274          275          276 
#>   6030049523   1743661714   1661556779   2217153987   2166714087   3072714240 
#>          277          278          279          280          281          282 
#>   1921147352   8127518724   2166455703   2377559139  31766807814  14949257520 
#>          283          284          285          286          287          288 
#>   3412885014   2601905419   2449982283   2357999546   2424492888   3280970396 
#>          289          290          291          292          293          294 
#>   5216282634   6367316717   3605342767   2163265191   3013467888   4862955295 
#>          295          296          297          298          299          300 
#>   2559945235   3387967665   3276736563  25908154322   1483762459   3804289476 
#>          301          302          303          304          305          306 
#>   4775177353   3591026048   2148211470   1744593098   1831923027   2009740622 
#>          307          308          309          310          311          312 
#>   3567212514   3625253229   2220797839   2375499785   2338311819   2615102940 
#>          313          314          315          316          317          318 
#>   2192381566   4508087460   1621312327   2133860826   5052679427   2536532199 
#>          319          320          321          322          323          324 
#> 146007505860   1962449250   3363469671   4545943702   1961704370   2000935825 
#>          325          326          327          328          329          330 
#>   2510704142   2342543118   2713363246  18757013689   3651687889   2749665556 
#>          331          332          333          334          335          336 
#>   2222287871   1724854506   6921218761   2366054284   4712728760   3495505598 
#>          337          338          339          340          341          342 
#>   4444097621   1479278287   3802656694    930517313   2493689718   1963609312 
#>          343          344          345          346          347          348 
#>   2348434367   2954200154   3228382707   1569560036   4465158201   4623279065 
#>          349          350          351          352          353          354 
#>   1758600754   2337653195   3210110998   2048231068   2476690901   1968637526 
#>          355          356          357          358          359          360 
#>   5014856049   1750142834   1864457876   1518543183   5683242499   1706532691 
#>          361          362          363          364          365          366 
#>   2571818210   1500873848   3654833591   6070891399   2325464476   2066917700 
#>          367          368          369          370          371          372 
#>   2878318193   1872006295   2700549644   1988748713   5398139158   2330773538 
#>          373          374          375          376          377          378 
#>   3071137878   3028056599   1961087036   3096475690   1997261459   2117700800 
#>          379          380          381          382          383          384 
#>   2444620161   2115146100   2412001706   1537954303   1598229329   1668620907 
#>          385          386          387          388          389          390 
#>   2827456282   6370062427   2001920741   2519354723   1529810255   2038746113 
#>          391          392          393          394          395          396 
#>   2525349139   4678300196   2011002209   2042890563   1994250883   4085893415 
#>          397          398          399          400          401          402 
#>   3794163586   5633470522   1424202457   -295560426   1833782532   2516409468 
#>          403          404          405          406          407          408 
#>   1906157543   2211615651   2340689973   1863061933   6954713274   1872311918 
#>          409          410          411          412          413          414 
#>   1862080237   1483237227   4055411312   4488132050   1651156236   1848387983 
#>          415          416          417          418          419          420 
#>  28322538300   2373609821   2050888075   3399926842   2766436141   1922285781 
#>          421          422          423          424          425          426 
#>   2280685707   1537892472   1865874697   2018800430   1681019274   2712702133 
#>          427          428          429          430          431          432 
#>   2432891479   2259990301   2387843405   6493582101   3232331128   2053730785 
#>          433          434          435          436          437          438 
#>   2855093526   2450356625   2101015982   6400353941   3050310999   4920835123 
#>          439          440          441          442          443          444 
#>   2081207683   1976291446   3086086355   3884436538   3060169256   2374815001 
#>          445          446          447          448          449          450 
#>   5844875558   1653741382   3244115531   2228836982   1970548791   2591805125 
#>          451          452          453          454          455          456 
#>   2503978687   2009457146   2974888414   1990086827   1757673969   2301908812 
#>          457          458          459          460          461          462 
#>   2167159433   2472007266   1886486960   2259476243   1407149304   2347276728 
#>          463          464          465          466          467          468 
#>    141172724   3303653827   3487598838   9680097038   1926929499   2255267306 
#>          469          470          471          472          473          474 
#>   2049789274  11917002690   3112463988   2292158779   1454157191   2263523104 
#>          475          476          477          478          479          480 
#>   5678500082   2050154680   2286290136   4847052394   2330403016   2490825230 
#>          481          482          483          484          485          486 
#>   2498656461   1807733159  15780262670   4297974472   2123052157   3509086912 
#>          487          488          489          490          491          492 
#>   3194660522   2006010146   2722974467   2001655582   3936295811   1512773344 
#>          493          494          495          496          497          498 
#>   1946858831    834674097   1718014879   2515423355   3076323544   1665462997 
#>          499          500          501          502          503          504 
#>   4621109438   3526850428   1690680507   3243166503   -458795512   2006356344 
#>          505          506          507          508          509          510 
#>   2012101091   1942935125   2954955838   2273472924   4454118751   2334741079 
#>          511          512          513          514          515          516 
#>   2521161438   1812173933   2113569713   2946579284   2492276514   2184165859 
#>          517          518          519          520          521          522 
#>   1796134285   2349525697   1633939511   1658904884   2033429295   3245651295 
#>          523          524          525          526          527          528 
#>   4860603003   9967393393   2264411367   2312922852   3680168227   3207432383 
#>          529          530          531          532          533          534 
#>   1332611642   1672351185   2818144387   1446168121   1839253367   1872310582 
#>          535          536          537          538          539          540 
#>   1779155038   1977804437   2773432291   2218685772   2175647421   2197195660 
#>          541          542          543          544          545          546 
#>   1944516381   2199842567   1985344398   2323239549   1576401331   3285798401 
#>          547          548          549          550          551          552 
#>   2508882980   1424874625   1856669474   2008221726   2474477210   2817754936 
#>          553          554          555          556          557          558 
#>   2125887405   2612557953   2123369184   2244771335   2073244643   2761754312 
#>          559          560          561          562          563          564 
#>   2740039070   2215619075   2306041894   1921146528   2095529655   2705120639 
#>          565          566          567          568          569          570 
#>   2389552571   1498878488   4090017282   1880757270   3220760957   1038821563 
#>          571          572          573          574          575          576 
#>   2040733718   5606460876   1499682804   2662793368   2737627364   2065617824 
#>          577          578          579          580          581          582 
#>   3827917027   2132152644   1940002604   1501627866   1922888410   2109013039 
#>          583          584          585          586          587          588 
#>   1738248743   2278152715   2683198224   4328299270   1966183466   1901842946 
#>          589          590          591          592          593          594 
#>   1695519142   2013193468   1995080156   1970247496   1942782840   -490073297 
#>          595          596          597          598          599          600 
#>   1977866302   2342280012   2213470246   1933141807   6516705709   2103221353 
#>          601          602          603          604          605          606 
#>   2242747414   2251743928   4791103784   2303723357   2206013560   2313155506 
#>          607          608          609          610          611          612 
#>   3719602501   2299999541   2016875281   3044661082   2576791357   2073955163 
#>          613          614          615          616          617          618 
#>   2120516561   2412012035    628192984   2658474155   2468518097   2134619380 
#>          619          620          621          622          623          624 
#>   4186153713   2085389995   2327091483   1581205054   2248141225   2030991651 
#>          625          626          627          628          629          630 
#>   2258447642   2287212876   2054282267   2001018856   2013987269   2421744781 
#>          631          632          633          634          635          636 
#>   2158532384   1993815342   2471458983   2147613539   2964744046   3053956029 
#>          637          638          639          640          641          642 
#>   1851773000   1426479014   3431144621   1978267114   1977858056   3180799579 
#>          643          644          645          646          647          648 
#>   3188788211   1880193281   1505968454   1542880980   2991127487   1965613177 
#>          649          650          651          652          653          654 
#>   2196341545   3279777217   1769799959   1943204726   1025685376   1835218890 
#>          655          656          657          658          659          660 
#>   2270923467   4101294033   2866819297   1983002999   2982260113   1979004532 
#>          661          662          663          664          665          666 
#>   2387370384   2088915410   4069775963   1909426190   1716987361   2685707628 
#>          667          668          669          670          671          672 
#>   1899731530   8182675387   2430938075   1945694209   2138368657   3144821006 
#>          673          674          675          676          677          678 
#>   2605496827   2546459448   1936216568   2198568987   2255605329   2496867926 
#>          679          680          681          682          683          684 
#>   2241652576   2005286983   2606974809   1989426801   2418193798   1875697587 
#>          685          686          687          688          689          690 
#>   2896028936   1725683893   2071912439   1934715974   2120950856   2184169920 
#>          691          692          693          694          695          696 
#>   2223675377   1979948382   2714908067   2020281575   2129165135   2046877312 
#>          697          698          699          700          701          702 
#>   1722968311   2528832014   2301752788   1956688724   2374649816   2008083110 
#>          703          704          705          706          707          708 
#>   1907312604   2024868964   2398475712   2340304510   2615837258   1838413986 
#>          709          710          711          712          713          714 
#>   2034479292   2682989259   1957085587   2417903958   1944443741   2012914434 
#>          715          716          717          718          719          720 
#>   2481361124   1963558190   2128150041   1924210811   2303165659   2236139055 
#>          721          722          723          724          725          726 
#>   1963298577   2013278722   2303179418   2093970527  12605340862   2492069055 
#>          727          728          729          730          731          732 
#>   2523779869   2347063229   2064590971   2070840688   1993802365   1894044090 
#>          733          734          735          736          737          738 
#>   1662140721   1975961334   2864631622   1895141666   2271346322   2518993712 
#>          739          740          741          742          743          744 
#>   2102763389   2035388795   1526763342   4918638805   2253043092   2075265439 
#>          745          746          747          748          749          750 
#>   2122005360   2101967317   1832607396   2007112749   2053533155   1922162377 
#>          751          752          753          754          755          756 
#>   1999180005   2484630165   2309469353   2166371816   2004475011   2195451678 
#>          757          758          759          760          761          762 
#>   2074980830   2303451185   2254835758   1170829350   2149871693   1845027032 
#>          763          764          765          766          767          768 
#>   2145521303   2179316605   5628074956   1942874758   2054971358   2149556761 
#>          769          770          771          772          773          774 
#>   1788468648   2070995867   8405546058   1940218659   1806094046   1651722846 
#>          775          776          777          778          779          780 
#>   2473769446   2054800014   1733123496   2230508801   1932570913   2485826509 
#>          781          782          783          784          785          786 
#>   2248611559   2213192895   2006597687   2131805712   2231451931   1979908504 
#>          787          788          789          790          791          792 
#>   2071024830   1658360125   1768015925   2854156150   2128907612   2040322087 
#>          793          794          795          796          797          798 
#>   2067727584   2316085756   2110943562   2173159071   1965209555   2053825357 
#>          799          800          801          802          803          804 
#>   1984047878   2053082848   1993436595   1834814072   2061275598   2035901595 
#>          805          806          807          808          809          810 
#>   2231370879   2296867282   2566570491   1923848759   2352236412   1832897943 
#>          811          812          813          814          815          816 
#>   2108771849   1841361973   2114887814   2126979974   1901175810   2187384893 
#>          817          818          819          820          821          822 
#>   2123456918   2274432147   2323990155   1992095938   4808023783   1967213667 
#>          823          824          825          826          827          828 
#>   2279589992   2035185836   2109396599   1944962732   2158674362   2144296685 
#>          829          830          831          832          833          834 
#>   1982412761   2087482882   3362515014   2006333036   1635091147   1943873480 
#>          835          836          837          838          839          840 
#>   2241132208   1843266090   2008525604   2058120426   2018731097   2324775761 
#>          841          842          843          844          845          846 
#>   1946822961   1986353211   2054736273   2300375959   2087347587   2197997911 
#>          847          848          849          850          851          852 
#>   2424793249   2059150049   2306642958   1952197168   2028894309   1966219592 
#>          853          854          855          856          857          858 
#>   1521202236   2594146630   2071844863   2117775757   2090967026   2003931148 
#>          859          860          861          862          863          864 
#>   2020693219   1860183558   1976464110   2293416322   1982076212   2122961751 
#>          865          866          867          868          869          870 
#>   2030612939   2129388321   2236298232   2030641479   2108039179   2060865854 
#>          871          872          873          874          875          876 
#>   1927876729   3627378863   1885104169   2088753999   2022215057   2190590290 
#>          877          878          879          880          881          882 
#>   1979734818   2139526610   2001827425   2014970527  37198980421   1797695552 
#>          883          884          885          886          887          888 
#>   1968205288   1849461923   1695261901   1853782514   2033209932   7199993241 
#>          889          890          891          892          893          894 
#>   2126794799   1999897305   2114511443   1695761615   3589720342   2058289363 
#>          895          896          897          898          899          900 
#>   1985011127   1974409651   2007323053   1980906668   2003105838   1941969433 
#>          901          902          903          904          905          906 
#>   2094163543   2042998649   1871549114  36556049486   1999533214   2646654919 
#>          907          908          909          910          911          912 
#>   2010888302   2090644312   1997919421   1963756882   2158556140   2120719225 
#>          913          914          915          916          917          918 
#>   1962218630   2023034818   2024871824   3710489527   2070028328   1994513439 
#>          919          920          921          922          923          924 
#>   1999723181   2066857410   1994375812   1953943912   2112493283    -89658187 
#>          925          926          927          928          929          930 
#>   1930760906   1990324402   2040483562   2001626253   1871618789   2025869706 
#>          931          932          933          934          935          936 
#>   2141222487   2038406560   1963807493   1994529761   1682646716   2023196187 
#>          937          938          939          940          941          942 
#>   2079496450   2198242147   1965420353   2088455510   1932284757   1973946279 
#>          943          944          945          946          947          948 
#>   1946168841   1960603409   1921386039   2007381672   1998347623   2027219553 
#>          949          950          951          952          953          954 
#>   1986274999   2046226654   2018530477   2236807379   1590176234   2262364553 
#>          955          956          957          958          959          960 
#>   2006913232   2097940707   1943819996   2087179812   2003330215   2105450313 
#>          961          962          963          964          965          966 
#>   1996370298   1147891102   2049563754   2684754054   2008914904   2028511789 
#>          967          968          969          970          971          972 
#>   2015952735   1986845122   2057690021   2906789608   2010417689   2000471323 
#>          973          974          975          976          977          978 
#>   2065039396   2097600396   1941482925   2041507657   2281837138   2036040406 
#>          979          980          981          982          983          984 
#>   2096108679   3253254257   2018596757   2237413405   2062304336   1949974552 
#>          985          986          987          988          989          990 
#>   1996624607   2040899980   2012308244   2002187793   1398147460   1854030427 
#>          991          992          993          994          995          996 
#>   2013231291   2035929728   2039149744   1927270264   2218176272   1960143153 
#>          997          998          999         1000         1001         1002 
#>   2195917613   1948703122   1992291028   2046925277   2071976411   2031322900 
#>         1003         1004         1005         1006         1007         1008 
#>   1952637442   1926432739   2061850993   2163843046   2068958154   2079920323 
#>         1009         1010         1011         1012         1013         1014 
#>   2014717771   1986155779   1964670087   2034352308   2034008892   2037152589 
#>         1015         1016         1017         1018         1019         1020 
#>   1854420126   1965554148   2077493690   1935192373   2022405369   2222344517 
#>         1021         1022         1023         1024         1025         1026 
#>   2035353928   2022958258   2018847273   1982199007   2090841598   2026637744 
#>         1027         1028         1029         1030         1031         1032 
#>   2058649545   2002411036   2106016937   2019203714   2021158007   2095525672 
#>         1033         1034         1035         1036         1037         1038 
#>   2010288182   2035943774   2044411983   1920609851   2080675252   1983751668 
#>         1039         1040         1041         1042         1043         1044 
#>   2134534838   2140548620   1958661504   1900412216 122355117197   2037437822 
#>         1045         1046         1047         1048 
#>   2016453503   2032989540   1924577430   2077957284

^{Created on 2021-01-21 by the reprex package (v0.3.0)}

DrMondesire commented 3 years ago

Thank you @aravindhebbali ! I pulled the latest dev and it worked for both_p() and both_aic(). I am now able to build the models and predict!

rsquaredacademy / olsrr

ols_step_both_p(): Error in if (pvals[minp] <= pent) {: argument is of length zero #175