smc_mallows_new_item_rank: SMC-Mallows new users rank

Description

Function to perform resample-move SMC algorithm where we receive a new item ranks from an existing user at each time step. Each correction and augmentation is done by filling in the missing item ranks using pseudolikelihood augmentation.

Usage

smc_mallows_new_item_rank(
  n_items,
  R_obs,
  N,
  Time,
  logz_estimate,
  mcmc_kernel_app,
  aug_rankings_init = NULL,
  rho_samples_init = NULL,
  alpha_samples_init = 0L,
  alpha = 0,
  alpha_prop_sd = 0.5,
  lambda = 0.1,
  alpha_max = 1e+06,
  aug_method = "random",
  verbose = FALSE,
  alpha_fixed = FALSE,
  metric = "footrule",
  leap_size = 1L
)
smc_mallows_new_item_rank_alpha_fixed(
  alpha,
  n_items,
  R_obs,
  metric,
  leap_size,
  N,
  Time,
  logz_estimate,
  mcmc_kernel_app,
  alpha_prop_sd,
  lambda,
  alpha_max,
  aug_method,
  verbose = FALSE
)

Value

a 3d matrix containing: the samples of: rho, alpha and the augmented rankings, and the effective sample size at each iteration of the SMC algorithm.

Arguments

n_items: Integer is the number of items in a ranking
R_obs: 3D matrix of size n_assessors by n_items by Time containing a set of observed rankings of Time time steps
N: Integer specifying the number of particles
Time: Integer specifying the number of time steps in the SMC algorithm
logz_estimate: Estimate of the partition function, computed with estimate_partition_function in the BayesMallow R package estimate_partition_function.
mcmc_kernel_app: Integer value for the number of applications we apply the MCMC move kernel
alpha: numeric value of the scale parameter.
alpha_prop_sd: Numeric value of the standard deviation of the prior distribution for alpha
lambda: Strictly positive numeric value specifying the rate parameter of the truncated exponential prior distribution of alpha.
alpha_max: Maximum value of alpha in the truncated exponential prior distribution.
aug_method: A character string specifying the approach for filling in the missing data, options are "pseudolikelihood" or "random"
verbose: Logical specifying whether to print out the progress of the SMC-Mallows algorithm. Defaults to FALSE.
alpha_fixed: Logical indicating whether to sample alpha or not.
metric: A character string specifying the distance metric to use in the Bayesian Mallows Model. Available options are "footrule", "spearman", "cayley", "hamming", "kendall", and "ulam".
leap_size: leap_size Integer specifying the step size of the leap-and-shift proposal distribution

Functions

smc_mallows_new_item_rank_alpha_fixed(): Deprecated function for smc_mallows_new_item_rank_alpha_fixed.