This function calculates the standard deviation of DATA for a a
fixed population mean MEAN. The result is the square root of the
corresponding variance function.
File: gsl-ref.info, Node: Absolute deviation, Next: Higher moments (skewness and kurtosis), Prev: Mean and standard deviation and variance, Up: Statistics
This function writes the ranges and bins of the histogram H
line-by-line to the stream STREAM using the format specifiers
RANGE_FORMAT and BIN_FORMAT. These should be one of the `%g',
`%e' or `%f' formats for floating point numbers. The function
returns 0 for success and `GSL_EFAILED' if there was a problem
writing to the file. The histogram output is formatted in three
columns, and the columns are separated by spaces, like this,
range[0] range[1] bin[0]
range[1] range[2] bin[1]
range[2] range[3] bin[2]
....
range[n-1] range[n] bin[n-1]
The values of the ranges are formatted using RANGE_FORMAT and the
value of the bins are formatted using BIN_FORMAT. Each line
contains the lower and upper limit of the range of the bins and the
value of the bin itself. Since the upper limit of one bin is the
lower limit of the next there is duplication of these values
between lines but this allows the histogram to be manipulated with
line-oriented tools.
- Function: int gsl_histogram_fscanf (FILE * STREAM, gsl_histogram * H)
This function reads formatted data from the stream STREAM into the
histogram H. The data is assumed to be in the three-column format
used by `gsl_histogram_fprintf'. The histogram H must be
preallocated with the correct length since the function uses the
size of H to determine how many numbers to read. The function
returns 0 for success and `GSL_EFAILED' if there was a problem
reading from the file.
File: gsl-ref.info, Node: Resampling from histograms, Next: The histogram probability distribution struct, Prev: Reading and writing histograms, Up: Histograms
Resampling from histograms
==========================
A histogram made by counting events can be regarded as a measurement
of a probability distribution. Allowing for statistical error, the
height of each bin represents the probability of an event where the
value of x falls in the range of that bin. The probability distribution
function has the one-dimensional form p(x)dx where,
p(x) = n_i/ (N w_i)
In this equation n_i is the number of events in the bin which contains
x, w_i is the width of the bin and N is the total number of events.
The distribution of events within each bin is assumed to be uniform.