## ----include = FALSE---------------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) ## ----setup-------------------------------------------------------------------- library(Colossus) library(data.table) ## ----eval=FALSE--------------------------------------------------------------- # Strat_Col <- "e" # e <- RunCoxRegression_Strata( # df, time1, time2, event, names, term_n, tform, keep_constant, # a_n, modelform, # control = control, strat_col = Strat_Col # ) ## ----eval=FALSE--------------------------------------------------------------- # Strat_Col <- c("e") # e <- RunPoissonRegression_Strata( # df, pyr, event, names, term_n, tform, keep_constant, # a_n, modelform, # control = control, strat_col = Strat_Col # ) ## ----eval=FALSE--------------------------------------------------------------- # e <- RunCoxRegression_Basic( # df, time1, time2, event, names, # keep_constant, a_n, # control = control # ) ## ----eval=FALSE--------------------------------------------------------------- # e <- RunCoxRegression_Single( # df, time1, time2, event, names, term_n, tform, # a_n, modelform, # control = control # ) # # e <- RunPoissonRegression_Single( # df, pyr, event, names, term_n, tform, # a_n, modelform, # control = control # ) ## ----eval=FALSE--------------------------------------------------------------- # pdata <- finegray(Surv(time2, event) ~ ., data = df) # # e <- RunCoxRegression_CR( # pdata, "fgstart", "fgstop", "fgstatus", names, term_n, tform, keep_constant, # a_n, modelform, # control = control, cens_weight = "fgwt" # ) ## ----eval=TRUE---------------------------------------------------------------- a <- c(0, 0, 0, 1, 1, 1) b <- c(1, 1, 1, 2, 2, 2) c <- c(0, 1, 2, 2, 1, 0) d <- c(1, 1, 0, 0, 1, 1) e <- c(0, 1, 1, 1, 0, 0) df <- data.table("t0" = a, "t1" = b, "e0" = c, "e1" = d, "fac" = e) time1 <- "t0" time2 <- "t1" df$pyr <- df$t1 - df$t0 pyr <- "pyr" events <- c("e0", "e1") ## ----eval=TRUE---------------------------------------------------------------- names_e0 <- c("fac") names_e1 <- c("fac") names_shared <- c("t0", "t0") term_n_e0 <- c(0) term_n_e1 <- c(0) term_n_shared <- c(0, 0) tform_e0 <- c("loglin") tform_e1 <- c("loglin") tform_shared <- c("quad_slope", "loglin_top") keep_constant_e0 <- c(0) keep_constant_e1 <- c(0) keep_constant_shared <- c(0, 0) a_n_e0 <- c(-0.1) a_n_e1 <- c(0.1) a_n_shared <- c(0.001, -0.02) name_list <- list("shared" = names_shared, "e0" = names_e0, "e1" = names_e1) term_n_list <- list("shared" = term_n_shared, "e0" = term_n_e0, "e1" = term_n_e1) tform_list <- list("shared" = tform_shared, "e0" = tform_e0, "e1" = tform_e1) keep_constant_list <- list( "shared" = keep_constant_shared, "e0" = keep_constant_e0, "e1" = keep_constant_e1 ) a_n_list <- list("shared" = a_n_shared, "e0" = a_n_e0, "e1" = a_n_e1) ## ----eval=TRUE---------------------------------------------------------------- Joint_Multiple_Events( df, events, name_list, term_n_list, tform_list, keep_constant_list, a_n_list ) ## ----eval=TRUE---------------------------------------------------------------- modelform <- "M" control <- list( "ncores" = 1, "lr" = 0.75, "maxiter" = 10, "halfmax" = 5, "epsilon" = 1e-6, "deriv_epsilon" = 1e-6, "verbose" = 2 ) Strat_Col <- "f" e <- RunPoissonRegression_Joint_Omnibus( df, pyr, events, name_list, term_n_list, tform_list, keep_constant_list, a_n_list, modelform, control = control, strat_col = Strat_Col ) Interpret_Output(e) ## ----eval=FALSE--------------------------------------------------------------- # a_n <- list(c(1, 1, 1), c(1, 2, 1), c(1, 2, 2), c(2, 1, 1)) # # # runs each (4) starts 1 iteration, and then runs the best 5 iterations # control$maxiter <- 5 # # runs each (4) starts 1 iteration, and then runs the best 5 iterations # control$maxiters <- c(1, 1, 1, 1, 5) # # runs each (4) starts 5 iterations, and then runs the best 5 iterations # control$maxiters <- c(5, 5, 5, 5, 5) # # e <- RunCoxRegression_Omnibus(df, time1, time2, event, # names, term_n, tform, keep_constant, # a_n, modelform, # control = control # )