@@ -212,7 +212,7 @@ class TimeSeasonality(Component):
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sigma_level_trend = pm.HalfNormal(
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"sigma_level_trend", sigma=1e-6, dims=ss_mod.param_dims["sigma_level_trend"]
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)
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- coefs_annual = pm.Normal("coefs_annual ", sigma=1e-2, dims=ss_mod.param_dims["coefs_annual "])
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+ params_annual = pm.Normal("params_annual ", sigma=1e-2, dims=ss_mod.param_dims["params_annual "])
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ss_mod.build_statespace_graph(data)
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idata = pm.sample(
@@ -298,10 +298,10 @@ def populate_component_properties(self):
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for endog_name in self .observed_state_names
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for state_name in self .provided_state_names
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]
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- self .param_names = [f"coefs_ { self .name } " ]
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+ self .param_names = [f"params_ { self .name } " ]
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self .param_info = {
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- f"coefs_ { self .name } " : {
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+ f"params_ { self .name } " : {
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"shape" : (k_states ,) if k_endog == 1 else (k_endog , k_states ),
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"constraints" : None ,
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"dims" : (f"state_{ self .name } " ,)
@@ -311,7 +311,7 @@ def populate_component_properties(self):
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}
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self .param_dims = {
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- f"coefs_ { self .name } " : (f"state_{ self .name } " ,)
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+ f"params_ { self .name } " : (f"state_{ self .name } " ,)
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if k_endog == 1
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else (f"endog_{ self .name } " , f"state_{ self .name } " )
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}
@@ -378,7 +378,7 @@ def make_symbolic_graph(self) -> None:
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self .ssm ["design" , :, :] = pt .linalg .block_diag (* [Z for _ in range (k_endog )])
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initial_states = self .make_and_register_variable (
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- f"coefs_ { self .name } " ,
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+ f"params_ { self .name } " ,
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shape = (k_unique_states ,) if k_endog == 1 else (k_endog , k_unique_states ),
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)
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if k_endog == 1 :
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