gamlssDS2 called by ds.gamlss

This is the second server-side aggregate function called by ds.gamlss.

Usage

gamlssDS2(
  parameter = parameter,
  family = family,
  data = data,
  mu.beta.vect = mu.beta.vect,
  sigma.beta.vect = sigma.beta.vect,
  nu.beta.vect = nu.beta.vect,
  tau.beta.vect = tau.beta.vect,
  control = control,
  i.control = i.control
)

Arguments

parameter

A string specifing for which of the distribution parameters c('mu', 'sigma', 'nu', 'tau') the model fitting should be performed.

family

A family string in the legal transmission format for DataSHIELD, which is used to define the distribution of the response variable. The DataSHIELD legal transmission format means that special characters, like '(' are replaced with the corresponding verbal descriptions, e.g. 'left_parenthesis'. Currently, only the following families are supported: family=c('NOleft_parenthesisright_parenthesis', 'NO2left_parenthesisright_parenthesis', 'BCCGleft_parenthesisright_parenthesis', 'BCPEleft_parenthesisright_parenthesis').

data

A character string specifying a data.frame object holding the data to be analysed under the specified model.

mu.beta.vect

A comma-separated string created by the client-side function specifying the vector of regression coefficients for mu at the current iteration.

sigma.beta.vect

A comma-separated string created by the client-side function specifying the vector of regression coefficients for sigma at the current iteration.

nu.beta.vect

A comma-separated string created by the client-side function specifying the vector of regression coefficients for nu at the current iteration.

tau.beta.vect

A comma-separated string created by the client-side function specifying the vector of regression coefficients for tau at the current iteration.

control

This sets the control parameters of the outer iterations algorithm using the gamlss.control function. This is a comma-separated string of 7 numeric values: (i) c.crit (the convergence criterion for the algorithm), (ii) n.cyc (the number of cycles of the algorithm), (iii) mu.step (the step length for the parameter mu), (iv) sigma.step (the step length for the parameter sigma), (v) nu.step (the step length for the parameter nu), (vi) tau.step (the step length for the parameter tau), (vii) gd.tol (global deviance tolerance level). The default values for these 7 parameters are set to control='0.001,20,1,1,1,1,Inf'.

i.control

This sets the control parameters of the inner iterations of the RS algorithm using the glim.control function. This is a comma-separated string of 4 numeric values: (i) cc (the convergence criterion for the algorithm), (ii) cyc (the number of cycles of the algorithm), (iii) bf.cyc (the number of cycles of the backfitting algorithm), (iv) bf.tol (the convergence criterion (tolerance level) for the backfitting algorithm). The default values for these 4 parameters are set to i.control='0.001,50,30,0.001'.

Value

A list with the following elements.

matrix

Numeric matrix that can be aggregated on the client-side to obtain the updated weighted least squares estimator for the distribution parameter.

vector

Numeric vector that can be aggregated on the client-side to obtain the updated weighted least squares estimator for the distribution parameter.

dv

Numeric value for the new deviance on the server.

disclosure.risk

Numeric value, either 0 or 1, whereby 1 indicates a disclosure risk.

errorMessage2

String for the disclosure risk. errorMessage='No errors' means that no disclosure risk was identified.

Details

It is an aggregation function that uses the model structure and starting parameter vectors constructed by gamlssDS1 to iteratively obtain the weighted least squares estimator for beta. The function gamlssDS2 also carries out a series of disclosure checks and if the arguments or data fail any of those tests, model construction is blocked and an appropriate server-side error message is created and returned to ds.gamlss on the client-side. This function is not intended for direct use by the user. For more details please see the extensive header of ds.gamlss.

Author

Annika Swenne