Module model_selection

source code

Module for selecting the best model.

Functions

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float

aic(chi2, k, n)
Akaike's Information Criteria (AIC).

source code

float

aicc(chi2, k, n)
Small sample size corrected AIC.

source code

float

bic(chi2, k, n)
Bayesian or Schwarz Information Criteria.

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select(method=None, modsel_pipe=None, pipes=None)
Model selection function.

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Variables

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__package__ = 'generic_fns'

Imports: log, get_type, has_pipe, pipe_names, switch, RelaxError, RelaxPipeError, get_specific_fn

Function Details

[hide private]

aic(chi2, k, n)

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Akaike's Information Criteria (AIC).

The formula is:

   AIC = chi2 + 2k

Parameters:

chi2 (float) - The minimised chi-squared value.
k (int) - The number of parameters in the model.
n (int) - The dimension of the relaxation data set.

Returns: float

The AIC value.

aicc(chi2, k, n)

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Small sample size corrected AIC.

The formula is:

                      2k(k + 1)
   AICc = chi2 + 2k + ---------
                      n - k - 1

Parameters:

chi2 (float) - The minimised chi-squared value.
k (int) - The number of parameters in the model.
n (int) - The dimension of the relaxation data set.

Returns: float

The AIC value.

bic(chi2, k, n)

source code

Bayesian or Schwarz Information Criteria.

The formula is:

   BIC = chi2 + k ln n

Parameters:

chi2 (float) - The minimised chi-squared value.
k (int) - The number of parameters in the model.
n (int) - The dimension of the relaxation data set.

Returns: float

The AIC value.

select(method=None, modsel_pipe=None, pipes=None)

source code

Model selection function.

Parameters:

method (str) - The model selection method. This can currently be one of:
- 'AIC', Akaike's Information Criteria.
- 'AICc', Small sample size corrected AIC.
- 'BIC', Bayesian or Schwarz Information Criteria.
- 'CV', Single-item-out cross-validation.
None of the other model selection techniques are currently supported.
modsel_pipe (str) - The name of the new data pipe to be created by copying of the selected data pipe.
pipes (list of str) - A list of the data pipes to use in the model selection.