apop_hist.c File Reference

Functions

• apop_model * apop_histogram_vector_reset (apop_model *template, gsl_vector *indata)
• apop_model * apop_histogram_model_reset (apop_model *base, apop_model *m, long int draws, gsl_rng *rng)
• apop_data * apop_histograms_test_goodness_of_fit (apop_model *m0, apop_model *m1)
• apop_data * apop_test_kolmogorov (apop_model *m1, apop_model *m2)
• void apop_histogram_normalize (apop_model *m)

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Detailed Description

PMF and CMF manipulations.

Copyright (c) 2006--2007 by Ben Klemens. Licensed under the modified GNU GPL v2; see COPYING and COPYING2. (Except psmirnov2x, Copyright R Project, but also licensed under the GPL.)

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Function Documentation

apop_model* apop_histogram_model_reset	(	apop_model *	base,
		apop_model *	m,
		long int	draws,
		gsl_rng *	rng
	)

Give me an existing histogram (i.e., an apop_model) and I'll create a new histogram with the same bins, but with data from draws random draws from the parametrized model you provide.

Unlike with most other histogram-genrating functions, this one will normalize the output to integrate to one. It uses the Designated initializers syntax for inputs.

Parameters:

	base	An apop_model produced using a form like apop_estimate(yourdata, apop_histogram). I.e. a histogram model to be used as a template. (No default)
	m	The model to be drawn from. Because this function works via random draws, the model needs to have a draw method. (No default)
	draws	The number of random draws to make. (arbitrary default = 1e5)
	rng	The gsl_rng used to make random draws. (default: see note on Auto-allocated RNGs)

void apop_histogram_normalize

(

apop_model *

m

)

Scale a histogram so it integrates to one (and is thus a proper PMF).

apop_model* apop_histogram_vector_reset	(	apop_model *	template,
		gsl_vector *	indata
	)

Give me an existing histogram (i.e., an apop_model) and I'll create a new histogram with the same bins, but with data from the vector you provide

Parameters:

	template	An apop_model produced using a form like apop_estimate(yourdata, apop_histogram).
	indata	The new data to be binned.

apop_data* apop_histograms_test_goodness_of_fit	(	apop_model *	m0,
		apop_model *	m1
	)

Test the goodness-of-fit between two histograms (in apop_model form). I assume that the histograms are aligned.

apop_data* apop_test_kolmogorov	(	apop_model *	m1,
		apop_model *	m2
	)

Run the Kolmogorov test to determine whether two distributions are identical.

Parameters:

m1,m2

Two matching apop_histograms, probably produced via apop_histogram_vector_reset or apop_histogram_model_reset.

Returns:

The -value from the Kolmogorov test that the two distributions are equal.