Main function in rds2 package. Returns the ML estimate of population size and degree distribution.

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Description

Performs maximum likelihood estimation of the population size, degree distribution and theta [explain] allowing (a) "soft" constraints on theta and (b) an input Sij matrix.

Usage

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  estimate.rds3(data, Sij, init, const, arc = FALSE,
    maxit = 10000, initial.thetas, theta.minimum,
    theta.range)

Arguments

data

An integer vector of the degrees of each individual sampled.

Sij

An integer matrix of the counts of individuals with rank j at sampling period t. Row names correspond to the degrees.

init

Optional initialization values.

const

Control the concentration of the mapping of the theta parameter from the contstrained domain to the real line.

arc

Should the degrees in the snowball be taken in account (TRUE) or just the size of the snowball (FALSE). Defaults to FALSE.

maxit

Number of maximal optimization iterations.

initial.thetas

Vector of initial values of theta parameter.

theta.minimum

Lower bound on the allowed values of theta.

theta.range

Allowed range of theta values. From theta.minimum to theta.minimum+range.

Author(s)

Jonathan Rosenblatt

Examples

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data(simulation)
temp.data<- unlist(data3[1,7000:7500])
estimate.rds3(temp.data, Sij = make.Sij(temp.data), initial.thetas = c(1,10), arc = FALSE, maxit = 1000, const = 0.5, theta.minimum = -0.5, theta.range = 2)