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BF: factors of sigma^2 were off #3

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BF: factors of sigma^2 were off #3

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10 changes: 4 additions & 6 deletions selectiveInference/R/funs.fixed.R
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Original file line number Diff line number Diff line change
Expand Up @@ -66,7 +66,6 @@ fixedLassoInf <- function(x, y, beta, lambda, family=c("gaussian","binomial","co

xnotm=x[,-vars]

# vars = which(abs(bbeta) > tol.beta / sqrt(colSums(x^2)))
nvar = length(vars)
if(nvar==0){
cat("Empty model",fill=T)
Expand Down Expand Up @@ -98,7 +97,7 @@ fixedLassoInf <- function(x, y, beta, lambda, family=c("gaussian","binomial","co
"glmnet with a lower setting of the",
"'thresh' parameter, for a more accurate convergence."))

MM = pinv(crossprod(xm))/sigma^2
MM = pinv(crossprod(xm))
# gradient at LASSO solution, first entry is 0 because intercept is unpenalized
# at exact LASSO solution it should be s2[-1]
gm = -g[vars]*lambda
Expand All @@ -115,7 +114,6 @@ fixedLassoInf <- function(x, y, beta, lambda, family=c("gaussian","binomial","co

if (p > n && type=="full") {


# Reorder so that active set is first
Xordered = cbind(xm,xnotm)

Expand All @@ -141,9 +139,9 @@ fixedLassoInf <- function(x, y, beta, lambda, family=c("gaussian","binomial","co

b1 = matrix(c(b1,rep(lambda,2*nrow(A0))),ncol=1)

# full covariance
# full covariance JT: covariance of what and what?
MMbr = (crossprod(xnotm) - t(xnotm)%*%xm%*%pinv(crossprod(xm))%*%t(xm)%*%xnotm)*sigma^2
MM = cbind(MM,matrix(0,nrow(MM),ncol(MMbr)))
MM = cbind(MM*sigma^2,matrix(0,nrow(MM),ncol(MMbr)))
MMbr = cbind(matrix(0,nrow(MMbr),nrow(MM)),MMbr)
MM = rbind(MM,MMbr)

Expand Down Expand Up @@ -174,7 +172,7 @@ fixedLassoInf <- function(x, y, beta, lambda, family=c("gaussian","binomial","co
sign[j] = sign(coef0[j])
vj = vj * sign[j]

limits.info = TG.limits(bbar, A1, b1, vj, Sigma=MM)
limits.info = TG.limits(bbar, A1, b1, vj, Sigma=MM*sigma^2)
if(is.null(limits.info)) return(list(pv=NULL,MM=MM,eta=vj))
a = TG.pvalue.base(limits.info, null_value=null_value[j], bits=bits)
pv[j] = a$pv
Expand Down