orthoDr_surv: IR-CP model In orthoDr: Semi-Parametric Dimension Reduction Models Using Orthogonality Constrained Optimization

Description

The counting process based semiparametric dimension reduction (IR-CP) model for right censored survival outcome.

Usage

 ```1 2 3``` ```orthoDr_surv(x, y, censor, method = "dm", ndr = ifelse(method == "forward", 1, 2), B.initial = NULL, bw = NULL, keep.data = FALSE, control = list(), maxitr = 500, verbose = FALSE, ncore = 0) ```

Arguments

 `x` A matrix or data.frame for features. The algorithm will not scale the columns to unit variance `y` A vector of observed time `censor` A vector of censoring indicator `method` Which estimating equation to use: should be `forward` (1-d model), `dn` (counting process) or `dm` (martingale) `ndr` The number of directions `B.initial` Initial `B` values. Will use the counting process based SIR model CP_SIR as the initial if leaving as `NULL`. If specified, must be a matrix with `ncol(x)` rows and `ndr` columns. Will be processed by Gram-Schmidt if not orthogonal `bw` A Kernel bandwidth, assuming each variables have unit variance `keep.data` Should the original data be kept for prediction. Default is `FALSE` `control` A list of tuning variables for optimization. `epsilon` is the size for numerically approximating the gradient. For others, see Wen and Yin (2013). `maxitr` Maximum number of iterations `verbose` Should information be displayed `ncore` Number of cores for parallel computing. The default is the maximum number of threads.

Value

A `orthoDr` object; a list consisting of

 `B` The optimal `B` value `fn` The final functional value `itr` The number of iterations `converge` convergence code

References

Sun, Q., Zhu, R., Wang, T. and Zeng, D. "Counting Process Based Dimension Reduction Method for Censored Outcomes." (2017) DOI: https://arxiv.org/abs/1704.05046.

Wen, Z. and Yin, W., "A feasible method for optimization with orthogonality constraints." Mathematical Programming 142.1-2 (2013): 397-434. DOI: https://doi.org/10.1007/s10107-012-0584-1

Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23``` ```# This is setting 1 in Sun et. al. (2017) with reduced sample size library(MASS) set.seed(1) N = 200; P = 6 V=0.5^abs(outer(1:P, 1:P, "-")) dataX = as.matrix(mvrnorm(N, mu=rep(0,P), Sigma=V)) failEDR = as.matrix(c(1, 0.5, 0, 0, 0, rep(0, P-5))) censorEDR = as.matrix(c(0, 0, 0, 1, 1, rep(0, P-5))) T = rexp(N, exp(dataX %*% failEDR)) C = rexp(N, exp(dataX %*% censorEDR - 1)) ndr = 1 Y = pmin(T, C) Censor = (T < C) # fit the model forward.fit = orthoDr_surv(dataX, Y, Censor, method = "forward") distance(failEDR, forward.fit\$B, "dist") dn.fit = orthoDr_surv(dataX, Y, Censor, method = "dn", ndr = ndr) distance(failEDR, dn.fit\$B, "dist") dm.fit = orthoDr_surv(dataX, Y, Censor, method = "dm", ndr = ndr) distance(failEDR, dm.fit\$B, "dist") ```

orthoDr documentation built on Sept. 5, 2019, 5:03 p.m.