# ICSKAT_fit_null.R Fit the null model (cubic basis spline for baseline cumulative hazard and coefficients for non-genetic coefficiens) for interval-censored skat. ```r ICSKAT_fit_null( init_beta, left_dmat, right_dmat, obs_ind, tpos_ind, lt, rt, runOnce = FALSE, checkpoint = FALSE, eps = 10^(-6) ) ``` ## Arguments - `init_beta`: (p+nknots+2)*1 vector of coefficients to initialize the Newton-Raphson. - `left_dmat`: n*(p+nknots+2) design matrix for left end of interval. - `right_dmat`: n*(p+nknots+2) design matrix for right end of interval. - `obs_ind`: n*1 vector of whether the event was observed before last follow-up. - `tpos_ind`: n*1 vector of whether the event was observed after follow-up started (t>0). - `lt`: n*1 vector of left interval times. - `rt`: n*1 vector of right interval times. - `runOnce`: Boolean tells the function to just go through the loop once instead of converging (to get quantites for bootstrapping). - `checkpoint`: Boolean tells the function to print when each iteration completes. - `eps`: Stop when the L2 norm of the difference in model coefficients reaches this limit. ## Returns A list with the elements: - **beta_fit**: (p+nknots+2)*1 vector of fitted coefficients under null model. - **iter**: Number of iterations needed to converge. - **Itt**: Fisher information matrix for the fitted coefficients. - **diff_beta**: Difference between beta_fit and previous iteration of the vector, can be checked for errors. - **err**: Value is 0 if no errors and 1 if Itt is singular, can't perform fit. - **errMsg**: Empty string if err=0, explains error if there is one. ## Examples ```r set.seed(2) xMat <- matrix(data=rnorm(200), nrow=100) bhFunInv <- function(x) {x} obsTimes <- 1:5 etaVec <- rep(0, 100) outcomeDat <- gen_IC_data(bhFunInv = bhFunInv, obsTimes = obsTimes, windowHalf = 0.1, probMiss = 0.1, etaVec = etaVec) lt <- outcomeDat$leftTimes rt <- outcomeDat$rightTimes tpos_ind <- as.numeric(lt > 0) obs_ind <- as.numeric(rt != Inf) dmats <- make_IC_dmat(xMat, lt, rt, obs_ind, tpos_ind) ICSKAT_fit_null(init_beta = rep(0, 5), left_dmat = dmats$left_dmat, right_dmat=dmats$right_dmat, obs_ind = obs_ind, tpos_ind = tpos_ind, lt = lt, rt = rt) ```

ICSKAT_fit_null function