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.TH pkstatascii 1 "06 December 2020" "" ""
.SH NAME
pkstatascii \- program to calculate basic statistics from text file
.SH SYNOPSIS
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.ad l
\fBpkstatascii\fR \kx
.if (\nx>(\n(.l/2)) .nr x (\n(.l/5)
'in \n(.iu+\nxu
\fB-i\fR \fIinput\fR [\fB-c\fR \fIcolumn\fR] [\fIoptions\fR] [\fIadvanced options\fR]
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'hy
.SH DESCRIPTION
\fBpkstatascii\fR calculates basic statistics of a data
series in a text file.
.SH OPTIONS
.TP 
\*(T<\fB\-i\fR\*(T> \fIfilename\fR, \*(T<\fB\-\-input\fR\*(T> \fIfilename\fR
name of the input text file
.TP 
\*(T<\fB\-size\fR\*(T>, \*(T<\fB\-\-size\fR\*(T>
sample size
.TP 
\*(T<\fB\-rnd\fR\*(T> \fInumber\fR, \*(T<\fB\-\-rnd\fR\*(T> \fInumber\fR
generate random numbers
.TP 
\*(T<\fB\-dist\fR\*(T> \fIfunction\fR, \*(T<\fB\-\-dist\fR\*(T> \fIfunction\fR
distribution for generating random numbers, see
http://www.gn/software/gsl/manual/gsl-ref_toc.html#TOC320
(only uniform and Gaussian supported yet)
.TP 
\*(T<\fB\-rnda\fR\*(T> \fIvalue\fR, \*(T<\fB\-\-rnda\fR\*(T> \fIvalue\fR
first parameter for random distribution
(mean value in case of Gaussian)
.TP 
\*(T<\fB\-rndb\fR\*(T> \fIvalue\fR, \*(T<\fB\-\-rndb\fR\*(T> \fIvalue\fR
second parameter for random distribution
(standard deviation in case of Gaussian)
.TP 
\*(T<\fB\-mean\fR\*(T>, \*(T<\fB\-\-mean\fR\*(T>
calculate mean
.TP 
\*(T<\fB\-median\fR\*(T>, \*(T<\fB\-\-median\fR\*(T>
calculate median
.TP 
\*(T<\fB\-var\fR\*(T>, \*(T<\fB\-\-var\fR\*(T>
calculate variance
.TP 
\*(T<\fB\-stdev\fR\*(T>, \*(T<\fB\-\-stdev\fR\*(T>
calculate standard deviation
.TP 
\*(T<\fB\-skew\fR\*(T>, \*(T<\fB\-\-skewness\fR\*(T>
calculate skewness
.TP 
\*(T<\fB\-kurt\fR\*(T>, \*(T<\fB\-\-kurtosis\fR\*(T>
calculate kurtosis
.TP 
\*(T<\fB\-sum\fR\*(T>, \*(T<\fB\-\-sum\fR\*(T>
calculate sum of column
.TP 
\*(T<\fB\-mm\fR\*(T>, \*(T<\fB\-\-minmax\fR\*(T>
calculate minimum and maximum value
.TP 
\*(T<\fB\-min\fR\*(T>, \*(T<\fB\-\-min\fR\*(T>
calculate minimum value
.TP 
\*(T<\fB\-max\fR\*(T>, \*(T<\fB\-\-max\fR\*(T>
calculate maximum value
.TP 
\*(T<\fB\-hist\fR\*(T>, \*(T<\fB\-\-hist\fR\*(T>
calculate histogram
.TP 
\*(T<\fB\-hist2d\fR\*(T>, \*(T<\fB\-\-hist2d\fR\*(T>
calculate 2-dimensional histogram based on two columns
.TP 
\*(T<\fB\-nbin\fR\*(T> \fIvalue\fR, \*(T<\fB\-\-nbin\fR\*(T> \fIvalue\fR
number of bins to calculate histogram
.TP 
\*(T<\fB\-rel\fR\*(T>, \*(T<\fB\-\-relative\fR\*(T>
use percentiles for histogram to calculate histogram
.TP 
\*(T<\fB\-kde\fR\*(T>, \*(T<\fB\-\-kde\fR\*(T>
Use
.URL http://pktools.nongnu.org/html/classKernel.html Kernel
density estimation when producing histogram.
The standard deviation is estimated based on Silverman's rule of
thumb
.TP 
\*(T<\fB\-cor\fR\*(T>, \*(T<\fB\-\-correlation\fR\*(T>
calculate Pearson produc-moment correlation coefficient between
two columns (defined by \*(T<\fB\-c\fR\*(T> <col1>
\*(T<\fB\-c\fR\*(T> <col2>)
.TP 
\*(T<\fB\-rmse\fR\*(T>, \*(T<\fB\-\-rmse\fR\*(T>
calculate root mean square error between two columns (defined by
\*(T<\fB\-c\fR\*(T> <col1> \*(T<\fB\-c\fR\*(T> <col2>)
.TP 
\*(T<\fB\-reg\fR\*(T>, \*(T<\fB\-\-regression\fR\*(T>
calculate linear regression between two columns and get
correlation coefficient (defined by
\*(T<\fB\-c\fR\*(T> <col1>
\*(T<\fB\-c\fR\*(T> <col2>)
.TP 
\*(T<\fB\-regerr\fR\*(T>, \*(T<\fB\-\-regerr\fR\*(T>
calculate linear regression between two columns and get root mean
square error (defined by \*(T<\fB\-c\fR\*(T> <col1>
\*(T<\fB\-c\fR\*(T> <col2>)
.TP 
\*(T<\fB\-v\fR\*(T> \fIlevel\fR, \*(T<\fB\-\-verbose\fR\*(T> \fIlevel\fR
verbose mode when positive
.PP
Advanced options
.TP 
\*(T<\fB\-src_min\fR\*(T> \fIvalue\fR, \*(T<\fB\-\-src_min\fR\*(T> \fIvalue\fR
start reading source from this minimum value
.TP 
\*(T<\fB\-src_max\fR\*(T> \fIvalue\fR, \*(T<\fB\-\-src_max\fR\*(T> \fIvalue\fR
stop reading source from this maximum value
.TP 
\*(T<\fB\-fs\fR\*(T> \fIseparator\fR, \*(T<\fB\-\-fs\fR\*(T> \fIseparator\fR
field separator.
.TP 
\*(T<\fB\-r\fR\*(T> \fIstartrow\fR [\*(T<\fB\-r\fR\*(T> \fIendrow\fR], \*(T<\fB\-\-range\fR\*(T> \fIstartrow\fR [\*(T<\fB\-\-range\fR\*(T> \fIendrow\fR]
rows to start/end reading.
Use \*(T<\fB\-r\fR\*(T> 1 \*(T<\fB\-r\fR\*(T> 10 to read first
10 rows where first row is header.
Use 0 to read all rows with no header.
.TP 
\*(T<\fB\-o\fR\*(T>, \*(T<\fB\-\-output\fR\*(T>
output the selected columns
.TP 
\*(T<\fB\-t\fR\*(T>, \*(T<\fB\-\-transpose\fR\*(T>
transpose input ascii vector
(use in combination with \*(T<\fB\-\-output\fR\*(T>)
.TP 
\*(T<\fB\-comment\fR\*(T> \fIcharacter\fR, \*(T<\fB\-\-comment\fR\*(T> \fIcharacter\fR
comment character