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Have most of the likelihood testing working, laplace likelihood parameters need fixing, some of the signs are wrong I believe

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This commit is contained in:
Alan Saul 2014-02-10 12:29:09 +00:00
parent 0f263d2ff2
commit fc44478ed2
1 changed files with 2 additions and 2 deletions
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4
GPy/inference/latent_function_inference/laplace.py
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@ -159,7 +159,7 @@ class LaplaceInference(object):
#Compute vival matrices for derivatives #Compute vival matrices for derivatives
dW_df = likelihood.d3logpdf_df3(f_hat, Y, extra_data=Y_metadata) # d3lik_d3fhat dW_df = likelihood.d3logpdf_df3(f_hat, Y, extra_data=Y_metadata) # d3lik_d3fhat
woodbury_vector = likelihood.dlogpdf_df(f_hat, Y, extra_data=Y_metadata) woodbury_vector = likelihood.dlogpdf_df(f_hat, Y, extra_data=Y_metadata)
dL_dfhat = 0.5*(np.diag(Ki_W_i)[:, None]*dW_df) #why isn't this -0.5? s2 in R&W p126 line 9. dL_dfhat = -0.5*(np.diag(Ki_W_i)[:, None]*dW_df) #why isn't this -0.5? s2 in R&W p126 line 9.
#BiK, _ = dpotrs(L, K, lower=1) #BiK, _ = dpotrs(L, K, lower=1)
#dL_dfhat = 0.5*np.diag(BiK)[:, None]*dW_df #dL_dfhat = 0.5*np.diag(BiK)[:, None]*dW_df
I_KW_i = np.eye(Y.shape[0]) - np.dot(K, K_Wi_i) I_KW_i = np.eye(Y.shape[0]) - np.dot(K, K_Wi_i)
@ -172,7 +172,7 @@ class LaplaceInference(object):
explicit_part = 0.5*(np.dot(Ki_f, Ki_f.T) - K_Wi_i) explicit_part = 0.5*(np.dot(Ki_f, Ki_f.T) - K_Wi_i)
#Implicit #Implicit
implicit_part = np.dot(woodbury_vector, dL_dfhat.T).dot(I_KW_i) implicit_part = -np.dot(woodbury_vector, dL_dfhat.T).dot(I_KW_i)
dL_dK = explicit_part + implicit_part dL_dK = explicit_part + implicit_part
else: else: