darts (version 1.0)

simpleEM: EM Algorithm for the Simple Model

Description

EM algorithm to estimate your variance based on your scores, in the simple model.

Usage

simpleEM(x, s.init = 100, niter = 100)

Arguments

x

Scores of throws aimed at the center of the dartboard.

s.init

The initial guess for the marginal variance.

niter

The number of iterations.

Value

s.final

The final estimate of the variance.

s.init

The initial estimate of the variance.

s

The estimate of the variance at each iteration of the EM algorithm.

loglik

The (observed) log likelihood at each iteration of the EM algorithm.

niter

The number of iterations.

Examples

# Scores of 100 of my dart throws, aimed at the center of the board
x = c(12,16,19,3,17,1,25,19,17,50,18,1,3,17,2,2,13,18,16,2,25,5,5,
1,5,4,17,25,25,50,3,7,17,17,3,3,3,7,11,10,25,1,19,15,4,1,5,12,17,16,
50,20,20,20,25,50,2,17,3,20,20,20,5,1,18,15,2,3,25,12,9,3,3,19,16,20,
5,5,1,4,15,16,5,20,16,2,25,6,12,25,11,25,7,2,5,19,17,17,2,12)

# Get my variance in the simple Gaussian model
a = simpleEM(x,niter=100)

# Check the log likelihood
plot(1:a$niter,a$loglik,type="l",xlab="Iteration",ylab="Log likelihood")

# The EM estimate of my variance
s = a$s.final