gamlssDS3 called by ds.gamlss — gamlssDS3 • dsGamlss

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

Usage

gamlssDS3(
  parameter = parameter,
  smoother = smoother,
  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,
  mu.gamma.vect = mu.gamma.vect,
  sigma.gamma.vect = sigma.gamma.vect,
  nu.gamma.vect = nu.gamma.vect,
  tau.gamma.vect = tau.gamma.vect,
  smoother.names = smoother.names,
  smoother.xl = smoother.xl,
  smoother.xr = smoother.xr,
  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.
smoother: An integer indicating the number of the smoother for the parameter that should be fitted.
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.
mu.gamma.vect: A comma-separated string created by the client-side function specifying the vector of smoothing regression coefficients for mu at the current iteration.
sigma.gamma.vect: A comma-separated string created by the client-side function specifying the vector of smoothing regression coefficients for sigma at the current iteration.
nu.gamma.vect: A comma-separated string created by the client-side function specifying the vector of smoothing regression coefficients for nu at the current iteration.
tau.gamma.vect: A comma-separated string created by the client-side function specifying the vector of smoothing regression coefficients for tau at the current iteration.
smoother.names: A string vector specifying the unique variable names for the smoother.
smoother.xl: A comma-separated string created by the client-side function specifying the left boundary for the knots for the smoother in smoother.names.
smoother.xr: A comma-separated string created by the client-side function specifying the right boundary for the knots for the smoother in smoother.names.
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 penalized weighted least squares estimator for the distribution parameter.
vector: Numeric vector that can be aggregated on the client-side to obtain the updated penalized weighted least squares estimator for the distribution parameter.
sumofsquares: Numeric value for the sum of squares for the old and new smoothing fitted values. This is needed on the client-side to determine the stopping criterion for backfitting.
sumofweights: Numeric value for the sum of weights. This is needed on the client-side to determine the stopping criterion for backfitting.

Details

It is an aggregation function that uses the model structure and starting parameter vectors constructed by gamlssDS1 to iteratively obtain the penalized weighted least squares estimator for gamma. 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