# adjZipf: parameter-adjusted Zipf

`adjZipf (-h -mU -kV -KW -EX -H -fY -gZ) text.spc`

Parameter-adjusted extended Zipf's law. Considers four link functions (linear, logarithmic, exponential, and power) and selects the optimal model for adjustment. Adjustment by hand of the selected model parameters is possible by means of the parameters f and g. Z is estimated by requiring that V(N) . For a detailed description of the output files, see lnreZipf.

input

`text.spc:` the frequency spectrum

`text.obs` should be available in the working directory.

options

`-h:` display on-line help

`-mU:` number of frequency ranks m in the fit is set to U (default: 15)

`-kV:` number of chunks for interpolation is set to V (default: 20)

`-KW:` number of chunks for extrapolation is set to W (default: 20)

`-EX:` extrapolation sample size is set to X (default: 2N_0)

`-H:` input file has no header (default: with header)

`-fY:` adjust intercept of link function by Y

`-gZ:` adjust slope of link function by Z

output

`text_aZ.spc:` expected frequency spectrum

`text_aZ.sp2:` expected frequency spectrum at 2N_0

`text_aZ.ev2:` V(N_0), E[V(N_0)] and E[V(2N_0)]

`text_aZ.int:` interpolation statistics

`text_aZ.ext:` extrapolation statistics

`text_aZ.sum:` summary of main statistics

`text_aZ.fit:` observed and expected developmental profiles of Z

`text_aZ.sta:` statistics for the goodness-of-fit of the link function

`t:` the t-statistic

`r:` the Pearson correlation r

`a:` the intercept of the (transformed) linear fit

`b:` the slope of the (transformed) linear fit

`obs:` linear link c(N)=a+bN

`log:` logarithmic link c(N)=a + b log(N)

`exp:` exponential link c(N)=e^{a + bN}

`pow:` power link c(N)=e^{a + b log(N)}

[ Previous | Index | Next ]