mfastLmCpp: Fast marginal simple regresion analyses
In MESS: Miscellaneous Esoteric Statistical Scripts

mfastLmCpp

R Documentation

Fast marginal simple regresion analyses

Description

Fast computation of simple regression slopes for each predictor represented by a column in a matrix

Usage

mfastLmCpp(y, x, addintercept = TRUE)

Arguments

`y`	A vector of outcomes.
`x`	A matrix of regressor variables. Must have the same number of rows as the length of y.
`addintercept`	A logical that determines if the intercept should be included in all analyses (TRUE) or not (FALSE)

Details

No error checking is done

Value

A data frame with three variables: coefficients, stderr, and tstat that gives the slope estimate, the corresponding standard error, and their ratio for each column in x.

Author(s)

Claus Ekstrom <claus@rprimer.dk>

Examples

## Not run: 
  // Generate 100000 predictors and 100 observations
  x <- matrix(rnorm(100*100000), nrow=100)
  y <- rnorm(100, mean=x[,1])
  mfastLmCpp(y, x)


## End(Not run)

MESS documentation built on Aug. 21, 2023, 1:05 a.m.