auxfuns: Internal functions and generics for 'mmsbm' package
In NetMix: Dynamic Mixed-Membership Network Regression Model

approxB

R Documentation

Internal functions and generics for `mmsbm` package

Description

These are various utilities and generic methods used by the main package function.

Usage

approxB(y, d_id, pi_mat, directed = TRUE)

getZ(pi_mat)

alphaLBound(par, tot_nodes, c_t, x_t, s_mat, t_id, var_beta, mu_beta)

alphaGrad(par, tot_nodes, c_t, x_t, s_mat, t_id, var_beta, mu_beta)

.cbind.fill(...)

.scaleVars(x, keep_const = TRUE)

.transf_muvar(orig, is_var, is_array, des.mat, nblock = NULL, nstate = NULL)

.bar.legend(colPalette, range)

.mpower(mat, p)

.findPerm(block_list, target_mat = NULL, use_perms = TRUE)

.transf(mat)

.compute.alpha(X, beta)

.vcovBeta(
  all_phi,
  beta_coef,
  n.sim,
  n.blk,
  n.hmm,
  n.nodes,
  n.periods,
  mu.beta,
  var.beta,
  est_kappa,
  t_id_n,
  X
)

.e.pi(alpha_list, kappa, C_mat = NULL)

.initPi(
  soc_mats,
  dyads,
  edges,
  nodes_pp,
  dyads_pp,
  n.blocks,
  periods,
  directed,
  ctrl
)

Arguments

`y, d_id, pi_mat, directed`	Internal arguments for blockmodel approximation.
`par`	Vector of parameter values.
`tot_nodes`	Integer vector; total number of nodes each node interacts with.
`c_t`	Integer matrix; samples from Poisson-Binomial counts of a node instantiating a group.
`x_t`	Numeric matrix; transposed monadic design matrices.
`s_mat`	Integer matrix; Samples of HMM states by time period.
`t_id`	Integer vector; for each node, what time-period is it observed in? zero-indexed.
`mu_beta, var_beta`	Numeric arrays; prior mean and variances of monadic coefficients.
`...`	Numeric vectors; vectors of potentially different length to be cbind-ed.
`x, keep_const`	Internal arguments for matrix scaling.
`orig`	Object to be transformed.
`is_var`	Boolean. Is the object to be transformed a variance term?
`is_array`	Boolean. Is the object to be transformed an array?
`des.mat`	Numeric matrix. Design matrix corresponding to transformed object.
`nblock`	Number of groups in model, defaults to `NULL`.
`nstate`	Number of hidden Markov states in model, defaults to `NULL`.
`colPalette`	A function produced by `colorRamp`.
`range`	The range of values to label the legend.
`mat`	Numeric matrix.
`p`	Numeric scalar; power to raise matrix to.
`block_list`	List of matrices; each element is a square, numeric matrix that defines a blockmodel,
`target_mat`	Numeric matrix; reference blockmodel that those in block_list should be aligned to. Optional, defaults to `NULL`.
`use_perms`	Boolean; should all row/column permutations be explored when realigning matrices? defaults to `TRUE`.
`X`	Numeric matrix; design matrix of monadic predictors.
`beta`	Numeric array; array of coefficients associated with monadic predictors. It of dimensions Nr. Predictors by Nr. of Blocks by Nr. of HMM states.
`all_phi, beta_coef, n.sim, n.blk, n.hmm, n.nodes, n.periods, mu.beta, var.beta, est_kappa, t_id_n,`	Additional internal arguments for covariance estimation.
`alpha_list`	List of mixed-membership parameter matrices.
`kappa`	Numeric matrix; matrix of marginal HMM state probabilities.
`C_mat`	Numeric matrix; matrix of posterior counts of block instantiations per node.
`soc_mats, dyads, edges, nodes_pp, dyads_pp, n.blocks, periods, ctrl`	Internal arguments for MM computation.

Details

These functions are meant for internal use only.

Value

See individual return section for each function:

.cbind.fill: Matrix of cbind'ed elements in ..., with missing values in each vector filled with NA.
.mpower: Matrix; the result of raising mat to the p power.
.findPerm: List of permuted blockmodel matrices.
.transf: Matrix with transformed mixed-membership vectors along its rows, s.t. no element is equal to 0.0 or 1.0.
.compute.alpha: List of predicted alpha matrices, one element per HMM state.
.e.pi: Matrix of predicted mixed-membership vectors along its rows, with expectation computed over marginal distribution over HMM states for each time period.
.missing: Transformed data.frame with missing values list-wise deleted, or expanded with missing indicator variables.
.createSocioB: List of sociomatrices.
.vertboot2: List of bootstrapped sociomatrices.