@@ -123,7 +123,7 @@ def sample(draws=500, step=None, init='auto', n_init=200000, start=None,
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Initialization method to use for auto-assigned NUTS samplers.
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* auto : Choose a default initialization method automatically.
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- Currently, this is `'unif +adapt_diag'`, but this can change in
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+ Currently, this is `'jitter +adapt_diag'`, but this can change in
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the future. If you depend on the exact behaviour, choose an
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initialization method explicitly.
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* adapt_diag : Start with a identity mass matrix and then adapt
@@ -311,8 +311,8 @@ def _check_start_shape(model, start):
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if var_shape :
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e += "\n Expected shape {} for var " \
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"'{}', got scalar {}" .format (
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- tuple (var_shape ), var .name , start [var .name ]
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- )
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+ tuple (var_shape ), var .name , start [var .name ]
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+ )
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if e != '' :
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raise ValueError ("Bad shape for start argument:{}" .format (e ))
@@ -699,7 +699,7 @@ def init_nuts(init='auto', njobs=1, n_init=500000, model=None,
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Initialization method to use.
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* auto : Choose a default initialization method automatically.
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- Currently, this is `'unif +adapt_diag'`, but this can change in
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+ Currently, this is `'jitter +adapt_diag'`, but this can change in
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the future. If you depend on the exact behaviour, choose an
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initialization method explicitly.
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* adapt_diag : Start with a identity mass matrix and then adapt
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