lnre.spc: Compute Expected Frequency Spectrum of LNRE Model (zipfR)

Description

lnre.spc computes the expected frequency spectrum of a LNRE model at specified sample size N, returning an object of class spc. Since almost all expected spectrum elements are non-zero, only an incomplete spectrum can be generated.

Usage

lnre.spc(model, N=NULL, variances=FALSE, m.max=100)

Arguments

model

an object belonging to a subclass of lnre, representing a LNRE model

a single positive integer, specifying the sample size \(N\) for which the expected frequency spectrum is calculated (defaults to same sample size as used for estimating the model)

variances

if TRUE, include variances for the spectrum elements in the spc object

m.max

number of spectrum elements listed in the frequency spectrum. The default of 100 is chosen to avoid numerical problems that certain LNRE models (in particular, GIGP) have for higher \(m\). If variance data is included, the default value is automatically reduced to 50.

Value

An object of class spc, representing the incomplete expected frequency spectrum of the LNRE model lnre at sample size N. If variances=TRUE, the spectrum also includes variance data.

Details

~~ TODO, if any ~~

Examples

Run this code

# NOT RUN {
## load Dickens dataset and compute lnre models
data(Dickens.spc)

zm <- lnre("zm",Dickens.spc)
fzm <- lnre("fzm",Dickens.spc, exact=FALSE)
gigp <- lnre("gigp",Dickens.spc)

## calculate the corresponding expected
## frequency spectra at the Dickens size
zm.spc <- lnre.spc(zm,N(Dickens.spc))
fzm.spc <- lnre.spc(fzm,N(Dickens.spc))
gigp.spc <- lnre.spc(gigp,N(Dickens.spc))

## comparative plot
plot(Dickens.spc,zm.spc,fzm.spc,gigp.spc,m.max=10)

## expected spectra at N=100e+8
## and comparative plot
zm.spc <- lnre.spc(zm,1e+8)
fzm.spc <- lnre.spc(fzm,1e+8)
gigp.spc <- lnre.spc(gigp,1e+8)

plot(zm.spc,fzm.spc,gigp.spc,m.max=10)

## with variances
zm.spc <- lnre.spc(zm,1e+8,variances=TRUE)
head(zm.spc)

## asking for more than 50 spectrum elements
## (increasing m.max will eventually lead
## to error, at different threshold for
## the different models)
zm.spc <- lnre.spc(zm,1e+8,m.max=1000)
fzm.spc <- lnre.spc(fzm,1e+8,m.max=1000)
gigp.spc <- lnre.spc(gigp,1e+8,m.max=100) ## gigp breaks first!


# }