To Do list

[julia-wrobel]

• [x] Edit sim_gfpca function to simulate Poisson, binary, or Gaussian data
• [x] unhard code K = 4 FPCs
• [x] return correct scores
• [x] check correct scaling of eigenfunctions, and make sure to be consistent for overlap vs. no overlap
• [x] index using seq(0, 1)
• [x] add in code to get eigenfunctions rather than using approx()
• [x] documentation for main functions
• [x] vignette
• [x] check compatibility with refund.shiny
• [x] currently breaks for some values of binwidth- play around with this
• [ ] Allow more general input (like a matrix) for Y
• [x] Use variable names that reflect Andrew's notation in the paper
• [ ] add progress bar for overlap = FALSE
• [ ] add unit tests
• [x] build in errors/ messages for poor input from the user
• [ ] Make sure code still works when input Y is not ordered by subject-domain
• [ ] remove unnecessary tidyverse functions (pipe, etc)
• [x] clean up binning code for overlap= TRUE option and be consistent with code used by Andrew in paper.
• [x] make sure user-specified arguments can be passed to fpca.face, bam, and glmer
• [ ] Add predict() function
• [ ] Add plot() function
• [ ]

[julia-wrobel]

For unit tests specifically, do

• [x] checks that simulation function works for all three families
• [x] check that fpca works for all three families- what behavior do we want for family = "gaussian"? Probably to tell people to use fpca. face and just return that.
• [x] check that multiple user inputs for binwidth work
• [ ] check that both npc and pve are valid arguments for gfpca function
• [x] check case 1 and case 2, overlap and no overlap
• [ ] check periodicity works