6.7.11.6.1. statsmodels.sandbox.regression.treewalkerclass.RU2NMNL¶

class statsmodels.sandbox.regression.treewalkerclass.RU2NMNL(endog, exog, tree, paramsind)[source]¶

Nested Multinomial Logit with Random Utility 2 parameterization

Parameters:

endog : array not used in this part exog : dict_like dictionary access to data where keys correspond to branch and leaf names. The values are the data arrays for the exog in that node. tree : nested tuples and lists each branch, tree or subtree, is defined by a tuple (branch_name, [subtree1, subtree2, ..., subtreek]) Bottom branches have as subtrees the list of leaf names. paramsind : dictionary dictionary that maps branch and leaf names to the names of parameters, the coefficients for exogs)

Notes

endog needs to be encoded so it is consistent with self.leaves, which defines the columns for the probability array. The ordering in leaves is determined by the ordering of the tree. In the dummy encoding of endog, the columns of endog need to have the same order as self.leaves. In the integer encoding, the integer for a choice has to correspond to the index in self.leaves. (This could be made more robust, by handling the endog encoding internally by leaf names, if endog is defined as categorical variable with associated category level names.)

Attributes

branches
leaves
paramsnames
parinddict

Methods

get_probs(params)

obtain the probability array given an array of parameters

__init__(endog, exog, tree, paramsind)[source]¶