lm_pi0 {swfdr}R Documentation

Estimation of pi0, proportion of p-values consistent with a null hypothesis

Description

Estimation of pi0, proportion of p-values consistent with a null hypothesis

Usage

lm_pi0(p, lambda = seq(0.05, 0.95, 0.05), X, type = c("logistic",
  "linear"), smooth.df = 3, threshold = TRUE,
  smoothing = c("unit.spline", "smooth.spline"))

Arguments

p

numeric vector, p-values

lambda

numeric vector, thresholds used to bin pvalues, must be in [0,1).

X

numeric matrix, covariates that might be related to p values (one test per row, one variable per column).

type

character, type of regression used to fit features to pvalues

smooth.df

Number of degrees of freedom when estimating pi0(x) with a smoother.

threshold

logical, if TRUE, all estimates are thresholded into unit interval; if FALSE, all estimates are left as they are computed

smoothing

character, type of smoothing used to fit pi0

Value

pi0 numerical vector of smoothed estimate of pi0(x). The length is the number of rows in X.

pi0.lambda numeric matrix of estimated pi0(x) for each value of lambda. The number of columns is the number of tests, the number of rows is the length of lambda.

lambda numeric vector of the thresholds used in calculating pi0.lambda

pi0.smooth (only output with smoothing="smooth.spline") Matrix of fitted values from the smoother fit to the pi0(x) estimates at each value of lambda (same number of rows and columns as pi0.lambda)

Examples

X <- seq(-1,2,length=1000) ##covariate
pi0 <- 1/4*X + 1/2 ##probability of being null
nullI <- rbinom(1000,prob=pi0,size=1)> 0 ##generate null/alternative p-values
pValues <- rep(NA,1000) ##vector of p-values
pValues[nullI] <- runif(sum(nullI)) ##null from U(0,1)
pValues[!nullI] <- rbeta(sum(!nullI),1,2) ##alternative from Beta
pi0x <- lm_pi0(pValues, X=X)


[Package swfdr version 1.12.0 Index]