# adjSich: parameter-adjusted GIGP (gamma = -0.5)

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

Parameter-adjusted inverse Gauss-Poisson model with gamma fixed at -0.5 apriori. Parameter estimation on the basis of cost function C_1. Considers four link functions (linear, logarithmic, exponential, and power) and selects the model that is optimal in the least squares sense for adjustment. Adjustment by hand of the selected model is possible by means of the parameters f and g. For a detailed description of the standard lnre output files, see lnreSich.

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 is set 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_aS.spc:` expected frequency spectrum

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

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

`text_aS.int:` interpolation statistics

`text_aS.ext:` extrapolation statistics

`text_aS.sum:` summary of main statistics

`text_aS.fit:` observed and expected developmental profiles of c

`text_aS.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)}

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