LinTransform: Transform parameters for linear transformations on response...

In IsingSampler: Sampling Methods and Distribution Functions for the Ising Model

Transform parameters for linear transformations on response catagories

Description

This function is mainly used to translate parameters estimated with response options set to 0 and 1 to a model in which the response options are -1 and 1, but can be used for any linear transformation of response options.

Usage

LinTransform(graph, thresholds, from = c(0L, 1L), to = c(-1L, 1L), a, b)

Arguments

graph	A matrix containing an Ising graph
thresholds	A vector containing thresholds
from	The original response encoding
to	The response encoding to transform to
a	The slope of the transformation. Overwrites to.
b	The intercept of the transformation. Overwrites to.

Author(s)

Sacha Epskamp <[e-mail]>

Examples

N <- 4 # Number of nodes

# Ising parameters:
Graph <- matrix(sample(0:1,N^2,TRUE,prob = c(0.7, 0.3)),N,N) * rnorm(N^2)
Graph <- pmax(Graph,t(Graph)) / N
diag(Graph) <- 0
Thresh <- -(rnorm(N)^2)
Beta <- 1

p1 <- IsingLikelihood(Graph, Thresh, Beta, c(0,1))

a <- 2
b <- -1

# p2 <- IsingLikelihood(Graph/(a^2), Thresh/a - (b*rowSums(Graph))/a^2, Beta, c(-1,1))

p2 <- IsingLikelihood(LinTransform(Graph,Thresh)$graph, 
                      LinTransform(Graph,Thresh)$thresholds , 
                      Beta, c(-1,1))
LinTransform

round(cbind(p1[,1],p2[,1]),5)

plot(p1[,1],p2[,1])
abline(0,1)

IsingSampler documentation built on Aug. 21, 2023, 5:13 p.m.