Module model_selection
source code
Module for selecting the best model.
float
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float
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float
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select(method=None,
modsel_pipe=None,
bundle=None,
pipes=None)
Model selection function. |
source code
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__package__ = ' generic_fns '
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Imports:
log,
sys,
generic_fns,
get_type,
has_pipe,
pipe_names,
switch,
RelaxError,
RelaxPipeError,
write_data,
get_specific_fn
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.
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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.
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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.
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select(method=None,
modsel_pipe=None,
bundle=None,
pipes=None)
| source code
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Model selection function.
- Parameters:
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