aldvmm.check: Checking the Validity of Objects Supplied to `aldvmm`

Description

aldvmm.check runs validity checks of objects supplied to aldvmm.

Usage

aldvmm.check(
  formula,
  data,
  subset,
  psi,
  ncmp,
  dist,
  optim.method,
  optim.control,
  optim.grad,
  init.method,
  init.est,
  init.lo,
  init.hi,
  se.fit,
  model,
  level,
  na.action,
  lcoef,
  lcpar,
  lcmp
)

Value

aldvmm.check returns warnings or stops the execution of

aldvmm if validity checks fail.

Arguments

formula: an object of class "formula" with a symbolic description of the model to be fitted. The model formula takes the form y ~ x1 + x2 | x1 + x4, where the | delimiter separates the model for expected values of normal distributions (left) and the multinomial logit model of probabilities of component membership (right).
data: a data frame, list or environment (or object coercible to a data frame by as.data.frame) including data on outcomes and explanatory variables in 'formula'.
subset: an optional numeric vector of row indices of the subset of the model matrix used in the estimation. 'subset' can be longer than the number of rows in data and include repeated values for re-sampling purposes.
psi: a numeric vector of minimum and maximum possible utility values smaller than or equal to 1 (e.g. c(-0.594, 0.883)). The potential gap between the maximum value and 1 represents an area with zero density in the value set from which utilities were obtained. The order of the minimum and maximum limits in 'psi' does not matter.
ncmp: a numeric value of the number of components that are mixed. The default value is 2. A value of 1 represents a tobit model with a gap between 1 and the maximum value in 'psi'.
dist: an optional character value of the distribution used in the components. In this release, only the normal distribution is available, and the default value is set to "normal".
optim.method: an optional character value of one of the following optimr methods: "Nelder-Mead", "BFGS", "CG", "L-BFGS-B", "nlminb", "Rcgmin", "Rvmmin" and "hjn". The default method is "BFGS". The method "L-BFGS-B" is used when lower and/or upper constraints are set using 'init.lo' and 'init.hi'. The method "nlm" cannot be used in the 'aldvmm' package.
optim.control: an optional list of optimr control parameters.
optim.grad: an optional logical value indicating if an analytical gradient should be used in optimr methods that can use this information. The default value is TRUE. If 'optim.grad' is set to FALSE, a finite difference approximation is used.
init.method: an optional character value indicating the method for obtaining initial values. The following values are available: "zero", "random", "constant" and "sann". The default value is "zero".
init.est: an optional numeric vector of user-defined initial values. User-defined initial values override the 'init.method' argument. Initial values have to follow the same order as parameter estimates in the return value 'coef'.
init.lo: an optional numeric vector of user-defined lower limits for constrained optimization. When 'init.lo' is not NULL, the optimization method "L-BFGS-B" is used. Lower limits of parameters have to follow the same order as parameter estimates in the return value 'coef'.
init.hi: an optional numeric vector of user-defined upper limits for constrained optimization. When 'init.hi' is not NULL, the optimization method "L-BFGS-B" is used. Upper limits of parameters have to follow the same order as parameter estimates in the return value 'coef'.
se.fit: an optional logical value indicating whether standard errors of fitted values are calculated. The default value is FALSE.
model: an optional logical value indicating whether the estimation data frame is returned in the output object. The default value is TRUE.
level: a numeric value of the significance level for confidence bands of fitted values. The default value is 0.95.
na.action: a character value passed to argument 'na.action' of the function model.frame in the preparation of the model matrix. The default value is "na.omit".
lcoef: a character vector of length 2 with labels of objects including regression coefficients of component distributions (default "beta") and coefficients of probabilities of component membership (default "delta").
lcpar: a character vector with the labels of objects including constant parameters of component distributions (e.g. the standard deviation of the normal distribution). The length of 'lcpar' depends on the distribution supplied to 'dist'.
lcmp: a character value representing a stub (default "Comp") for labeling objects including regression coefficients in different components (e.g. "Comp1", "Comp2", ...). This label is also used in summary tables returned by summary.aldvmm.

Details

aldvmm.check checks the validity of arguments of aldvmm.