Error in { : task 28 failed - "non-conformable arrays"

[Ernest861]

System: Macbook M2Max 96GB R: 4.4.1 mnet: 0.14 data: data.table all vars are num

` zVars <- c("WeChat", "XiaoHongShu", "HonorofKings","PUBG", "Douyin", "Taobao","PDD", "Desktop", "Novel", "Education")

zData_summary2 str(zData_summary2) Classes ‘data.table’ and 'data.frame': 9669 obs. of 14 variables: $ id : num 5 5 5 5 5 5 5 5 5 5 ... $ hou : num 0 0 0 0 1 1 1 5 5 6 ... $ quarter : num 0 1 2 3 0 1 2 2 3 0 ... $ group : num 1 1 1 1 1 1 1 1 1 1 ... $ WeChat : num 0.1 0 0 0 0 ... $ XiaoHongShu : num 0 0 0 0 0 0 0 0 0 0 ... $ HonorofKings: num 0 0 0 0 0 0 0 0 0 0 ... $ PUBG : num 0 0 0 0 0 0 0 0 0 0 ... $ Douyin : num 0 0 0 0 0 0 0 0 0 0 ... $ Taobao : num 0 0 0 0 0 0 0 0 0 0 ... $ PDD : num 0 0 0 0 0 0 0 0 0 0 ... $ Desktop : num 1 1 1 1 1 1 1 1 1 1 ... $ Novel : num 0 0 0 0 0 0 0 0 0 0 ... $ Education : num 0 0 0 0 0 0 0 0 0 0 ...

• attr(*, ".internal.selfref")= `

output <- mlVAR_GC(data = zData_summary2,

• vars = zVars,
• idvar = "id",
• dayvar = "hou",
• beepvar = "quarter",
• groups = "group",
• nP = 20,
• contemporaneous = "orthogonal",
• temporal = "orthogonal",
• nCores = 12,
• pbar = TRUE) | | 0%starting worker pid=57424 on localhost:11240 at 20:56:15.300 starting worker pid=57437 on localhost:11240 at 20:56:15.442 starting worker pid=57450 on localhost:11240 at 20:56:15.590 starting worker pid=57471 on localhost:11240 at 20:56:15.725 starting worker pid=57484 on localhost:11240 at 20:56:15.892 starting worker pid=57497 on localhost:11240 at 20:56:16.030 starting worker pid=57510 on localhost:11240 at 20:56:16.197 starting worker pid=57523 on localhost:11240 at 20:56:16.352 starting worker pid=57536 on localhost:11240 at 20:56:16.511 starting worker pid=57549 on localhost:11240 at 20:56:16.659 starting worker pid=57562 on localhost:11240 at 20:56:16.814 starting worker pid=57575 on localhost:11240 at 20:56:17.018 Loading required package: mnet Loading required package: mnet Loading required package: mnet Loading required package: mnet Loading required package: mnet Loading required package: mnet Loading required package: mnet Loading required package: mnet Loading required package: mnet Loading required package: mnet Loading required package: mnet Loading required package: mnet This is mnet 0.1.4 Please report issues on Github: https://github.com/jmbh/mnet/issues loaded mnet and set parent environment This is mnet 0.1.4 Please report issues on Github: https://github.com/jmbh/mnet/issues loaded mnet and set parent environment This is mnet 0.1.4 Please report issues on Github: https://github.com/jmbh/mnet/issues loaded mnet and set parent environment This is mnet 0.1.4 Please report issues on Github: https://github.com/jmbh/mnet/issues loaded mnet and set parent environment This is mnet 0.1.4 Please report issues on Github: https://github.com/jmbh/mnet/issues loaded mnet and set parent environment This is mnet 0.1.4 Please report issues on Github: https://github.com/jmbh/mnet/issues loaded mnet and set parent environment This is mnet 0.1.4 Please report issues on Github: https://github.com/jmbh/mnet/issues This is mnet 0.1.4 Please report issues on Github: https://github.com/jmbh/mnet/issues loaded mnet and set parent environment loaded mnet and set parent environment This is mnet 0.1.4 Please report issues on Github: https://github.com/jmbh/mnet/issues loaded mnet and set parent environment This is mnet 0.1.4 Please report issues on Github: https://github.com/jmbh/mnet/issues loaded mnet and set parent environment This is mnet 0.1.4 Please report issues on Github: https://github.com/jmbh/mnet/issues loaded mnet and set parent environment This is mnet 0.1.4 Please report issues on Github: https://github.com/jmbh/mnet/issues loaded mnet and set parent environment |======================================================================================================================================================================================= | 95%Warning message: In mlVAR(data = l_data_h0[[j]], vars = vars, idvar = idvar, estimator = estimator, : 1 subjects detected with < 20 measurements. This is not recommended, as within-person centering with too few observations per subject will lead to biased estimates (most notably: negative self-loops). Warning messages: 1: In mlVAR(data = l_data_h0[[j]], vars = vars, idvar = idvar, estimator = estimator, : 1 subjects detected with < 20 measurements. This is not recommended, as within-person centering with too few observations per subject will lead to biased estimates (most notably: negative self-loops). Warning messages: 2: In mlVAR(data = l_data_h0[[j]], vars = vars, idvar = idvar, estimator = estimator, : 1 subjects detected with < 20 measurements. This is not recommended, as within-person centering with too few observations per subject will lead to biased estimates (most notably: negative self-loops). Warning message: 1: In mlVAR(data = l_data_h0[[j]], vars = vars, idvar = idvar, estimator = estimator, : 1 subjects detected with < 20 measurements. This is not recommended, as within-person centering with too few observations per subject will lead to biased estimates (most notably: negative self-loops). In mlVAR(data = l_data_h0[[j]], vars = vars, idvar = idvar, estimator = estimator, : 1 subjects detected with < 20 measurements. This is not recommended, as within-person centering with too few observations per subject will lead to biased estimates (most notably: negative self-loops). Warning messages: 2: 1: In mlVAR(data = l_data_h0[[j]], vars = vars, idvar = idvar, estimator = estimator, : 1 subjects detected with < 20 measurements. This is not recommended, as within-person centering with too few observations per subject will lead to biased estimates (most notably: negative self-loops). In mlVAR(data = l_data_h0[[j]], vars = vars, idvar = idvar, estimator = estimator, : 1 subjects detected with < 20 measurements. This is not recommended, as within-person centering with too few observations per subject will lead to biased estimates (most notably: negative self-loops). 2: In mlVAR(data = l_data_h0[[j]], vars = vars, idvar = idvar, estimator = estimator, : 1 subjects detected with < 20 measurements. This is not recommended, as within-person centering with too few observations per subject will lead to biased estimates (most notably: negative self-loops). Warning messages: Warning messages: 1: In mlVAR(data = l_data_h0[[j]], vars = vars, idvar = idvar, estimator = estimator, : 1 subjects detected with < 20 measurements. This is not recommended, as within-person centering with too few observations per subject will lead to biased estimates (most notably: negative self-loops). 2: In mlVAR(data = l_data_h0[[j]], vars = vars, idvar = idvar, estimator = estimator, : 1 subjects detected with < 20 measurements. This is not recommended, as within-person centering with too few observations per subject will lead to biased estimates (most notably: negative self-loops). 1: In mlVAR(data = l_data_h0[[j]], vars = vars, idvar = idvar, estimator = estimator, : 1 subjects detected with < 20 measurements. This is not recommended, as within-person centering with too few observations per subject will lead to biased estimates (most notably: negative self-loops). 2: In mlVAR(data = l_data_h0[[j]], vars = vars, idvar = idvar, estimator = estimator, : 1 subjects detected with < 20 measurements. This is not recommended, as within-person centering with too few observations per subject will lead to biased estimates (most notably: negative self-loops). Warning message: In mlVAR(data = l_data_h0[[j]], vars = vars, idvar = idvar, estimator = estimator, : 1 subjects detected with < 20 measurements. This is not recommended, as within-person centering with too few observations per subject will lead to biased estimates (most notably: negative self-loops). Warning messages: 1: In mlVAR(data = l_data_h0[[j]], vars = vars, idvar = idvar, estimator = estimator, : 1 subjects detected with < 20 measurements. This is not recommended, as within-person centering with too few observations per subject will lead to biased estimates (most notably: negative self-loops). 2: In mlVAR(data = l_data_h0[[j]], vars = vars, idvar = idvar, estimator = estimator, : 1 subjects detected with < 20 measurements. This is not recommended, as within-person centering with too few observations per subject will lead to biased estimates (most notably: negative self-loops). Warning message: In mlVAR(data = l_data_h0[[j]], vars = vars, idvar = idvar, estimator = estimator, : 1 subjects detected with < 20 measurements. This is not recommended, as within-person centering with too few observations per subject will lead to biased estimates (most notably: negative self-loops). Warning messages: 1: In mlVAR(data = l_data_h0[[j]], vars = vars, idvar = idvar, estimator = estimator, : 1 subjects detected with < 20 measurements. This is not recommended, as within-person centering with too few observations per subject will lead to biased estimates (most notably: negative self-loops). 2: In mlVAR(data = l_data_h0[[j]], vars = vars, idvar = idvar, estimator = estimator, : 1 subjects detected with < 20 measurements. This is not recommended, as within-person centering with too few observations per subject will lead to biased estimates (most notably: negative self-loops). Warning messages: 1: In mlVAR(data = l_data_h0[[j]], vars = vars, idvar = idvar, estimator = estimator, : 1 subjects detected with < 20 measurements. This is not recommended, as within-person centering with too few observations per subject will lead to biased estimates (most notably: negative self-loops). 2: In mlVAR(data = l_data_h0[[j]], vars = vars, idvar = idvar, estimator = estimator, : 1 subjects detected with < 20 measurements. This is not recommended, as within-person centering with too few observations per subject will lead to biased estimates (most notably: negative self-loops). |================================================================================================================================================================================================| 100%Warning messages: 1: In e$fun(obj, substitute(ex), parent.frame(), e$data) : already exporting variable(s): m_data_cmb, vars, idvar, estimator, contemporaneous, temporal, totalN, v_Ns, v_ids, pb, pbar, dayvar, beepvar, paired 2: In mlVAR(data = l_data[[j]], vars = vars, idvar = idvar, estimator = estimator, : 1 subjects detected with < 20 measurements. This is not recommended, as within-person centering with too few observations per subject will lead to biased estimates (most notably: negative self-loops).

  output <- mlVAR_GC(data = zData_summary2,

• vars = zVars,
• idvar = "id",
• dayvar = "hou",
• beepvar = "quarter",
• groups = "group",
• nP = 100,
• contemporaneous = "orthogonal",
• temporal = "orthogonal",
• nCores = 12,
• pbar = TRUE) | | 0%starting worker pid=64183 on localhost:11240 at 21:23:37.890 starting worker pid=64196 on localhost:11240 at 21:23:38.042 starting worker pid=64209 on localhost:11240 at 21:23:38.177 starting worker pid=64222 on localhost:11240 at 21:23:38.321 starting worker pid=64235 on localhost:11240 at 21:23:38.449 starting worker pid=64257 on localhost:11240 at 21:23:38.606 starting worker pid=64270 on localhost:11240 at 21:23:38.748 starting worker pid=64284 on localhost:11240 at 21:23:38.890 starting worker pid=64297 on localhost:11240 at 21:23:39.050 starting worker pid=64310 on localhost:11240 at 21:23:39.214 starting worker pid=64323 on localhost:11240 at 21:23:39.375 starting worker pid=64336 on localhost:11240 at 21:23:39.554 Loading required package: mnet Loading required package: mnet Loading required package: mnet Loading required package: mnet Loading required package: mnet Loading required package: mnet Loading required package: mnet Loading required package: mnet Loading required package: mnet Loading required package: mnet Loading required package: mnet Loading required package: mnet This is mnet 0.1.4 Please report issues on Github: https://github.com/jmbh/mnet/issues This is mnet 0.1.4 Please report issues on Github: https://github.com/jmbh/mnet/issues loaded mnet and set parent environment loaded mnet and set parent environment This is mnet 0.1.4 Please report issues on Github: https://github.com/jmbh/mnet/issues loaded mnet and set parent environment This is mnet 0.1.4 Please report issues on Github: https://github.com/jmbh/mnet/issues loaded mnet and set parent environment This is mnet 0.1.4 Please report issues on Github: https://github.com/jmbh/mnet/issues loaded mnet and set parent environment This is mnet 0.1.4 This is mnet 0.1.4 Please report issues on Github: https://github.com/jmbh/mnet/issues Please report issues on Github: https://github.com/jmbh/mnet/issues loaded mnet and set parent environment loaded mnet and set parent environment This is mnet 0.1.4 Please report issues on Github: https://github.com/jmbh/mnet/issues loaded mnet and set parent environment This is mnet 0.1.4 Please report issues on Github: https://github.com/jmbh/mnet/issues loaded mnet and set parent environment This is mnet 0.1.4 Please report issues on Github: https://github.com/jmbh/mnet/issues loaded mnet and set parent environment This is mnet 0.1.4 Please report issues on Github: https://github.com/jmbh/mnet/issues loaded mnet and set parent environment This is mnet 0.1.4 Please report issues on Github: https://github.com/jmbh/mnet/issues loaded mnet and set parent environment |============================================================================================================================================================================================== | 99%Error in { : task 28 failed - "non-conformable arrays" In addition: Warning message: In e$fun(obj, substitute(ex), parent.frame(), e$data) : already exporting variable(s): m_data_cmb, vars, idvar, estimator, contemporaneous, temporal, totalN, v_Ns, v_ids, pb, pbar, dayvar, beepvar, paired

[jmbh]

Thanks for reporting this. Any chance you could provide a reproducible example of this?

[Ernest861]

Hi Jonas, Thanks for your replay and package. I attached my code and data. zTestMLVARGC.zip