simlm: The simlm() function quickly simulates data from a basic...

In mikejacktzen/datzen:

Description

Each of the n noise elements are from rnorm(mean=0,sd=1).

Except for columns 1 and 2, each of the design-matrix elements are from runif(min=0,max=1).

The outcome y is noise added to the linear combination of the design matrix with 'coef_true'.

Usage

simlm(n = 10, p = 4, coef_true = seq(1:p), seed = NULL,
  output_meta = FALSE)

Arguments

n	integer for number of observations
p	integer for total number of cols in the design matrix. Note, offset from '3:p'. Since col 1 is reserved for intercept-column of 1s and col 2 is reserved for treatment-column of 1s/0s
coef_true	vector (length p) for true lm coefficients
seed	a seed for RNG (default NULL)
output_meta	a logical (default FALSE) determining if meta info is returned as list elements

Value

If 'output_meta=FALSE' (the default), only the data.frame 'yx' is returned. The column names of yx are names(yx)=c('y',paste0("x",seq(1:p))).

If 'output_meta=TRUE', a 3 element list with yx, coef_true, noise.

Examples

simlm()

out = simlm(n=1000,p=10)
lm(data=out,y~-1+.)

out = simlm(n=1000,seed=123)
lm(data=out,y~-1+.)

out = simlm(n=1000,seed=123,output_meta=TRUE)
str(out)

out = simlm(p=3,n=100,coef_true = c(69,23,7),output_meta=TRUE)
lm(data=out$yx[,-2], y ~ 1+.)

mikejacktzen/datzen documentation built on June 14, 2019, 5:23 p.m.