posterior: Posterior Means - calculating the posterior value of HZINB...
In sidiwang/hgzips: hgzips

Description Usage Arguments Value

Posterior Means - calculating the posterior value of HZINB a1_j, b1_j, a2_j, b2_j, pi_j and omega_j

posterior_abol_two_gamma(
  grid_a1,
  grid_b1,
  grid_a2,
  grid_b2,
  grid_pi,
  grid_omega = NULL,
  pi_klh_final_a1_j,
  pi_klh_final_b1_j,
  pi_klh_final_a2_j,
  pi_klh_final_b2_j,
  pi_klh_final_pi_j,
  pi_klh_final_omega_j = NULL,
  N_ij,
  E_ij,
  zeroes = FALSE,
  N_star = 1
)

posterior_abol(
  grid_a,
  grid_b,
  grid_omega = NULL,
  pi_klh_final_a_j,
  pi_klh_final_b_j,
  pi_klh_final_omega_j = NULL,
  pi_klh = NULL,
  N_ij,
  E_ij,
  dataset = NULL,
  zeroes = FALSE,
  N_star = 1
)

Posteror_ZINB_two_gamma(alpha1, beta1, alpha2, beta2, pi, omega, N, E)

post_mean_lambda_ZINB(alpha, beta, N, E)

post_mean_loglambda_ZINB(alpha, beta, N, E)

Posteror_MGPS(alpha1, beta1, alpha2, beta2, pi, N, E)

Posteror_MGPS_log(alpha1, beta1, alpha2, beta2, pi, N, E)

`grid_omega`	omega value grid
`pi_klh_final_omega_j`	final estimation of the probability of each omega value (HZINB, assuming a_j, b_j and omega_j are independent from each other), produced by the EM algorithm (use pi_klh_final_omega_j = NULL if it's an independent case)
`N_ij`	matrix of N_ij, i = AE, j = drugs
`E_ij`	matrix of E_ij, i = AE, j = drugs
`zeroes`	A logical scalar specifying if zero counts should be included.
`N_star`	the minimum Nij count size to be used for hyperparameter estimation. If zeroes are included in Nij vector, please set N_star = NULL
`grid_a`	alpha value grid
`grid_b`	beta value grid
`pi_klh_final_a_j`	final estimation of the probability of each alpha value (HZINB, assuming a_j, b_j and omega_j are independent from each other), produced by the EM algorithm (use pi_klh_final_a_j = NULL if it's an independent case)
`pi_klh_final_b_j`	final estimation of the probability of each beta value (HZINB, assuming a_j, b_j and omega_j are independent from each other), produced by the EM algorithm (use pi_klh_final_b_j = NULL if it's an independent case)
`pi_klh`	final estimation of the probability of each a_j - b_j - omega_j combination (HZINB, not assuming independence), produced by the EM algorithm (use pi_klh = NULL if it's an independent case)
`dataset`	a list of squashed datasets that include N_ij, E_ij and weights for each drug (j). This dataset list can be generated by the rawProcessing function in this package. (use dataset = NULL if it's an unsquashed case)