emProbLL: Calculate the probability of LL classification from an EM...

In cookpa/socialdefeat: Methods for analyzing social defeat data

Description

Classifies new data using a pre-existing Gaussian mixture from an object of type Mclust.

Usage

emProbLL(clusters, latency)

Arguments

clusters	An object of class Mclust, which should contain a two-class Gaussian mixture model fit to average latency data.
latency	A vector of average latencies. The probability of LL classification is computed for each entry.

Value

A vector containing LL probabilities for each input latency.

Author(s)

Philip A Cook <[e-mail]>

Examples

set.seed(20140123)

sl <- rnorm(60, 200, 100)
sl[which(sl < 0)] <- 0

ll <- rnorm(15, 600, 100)
ll[which(ll > 900)] <- 900

latency = c(sl, ll)

library(mclust)

clusters = Mclust(latency, G=2)

emProbLL(clusters, c(300, 400, 500))

cookpa/socialdefeat documentation built on May 17, 2019, 10:12 p.m.