gamlssDS6 called by ds.gamlss — gamlssDS6 • dsGamlss

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

Usage

gamlssDS6(
  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,
  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,
  autostep = autostep,
  inner.iteration.count = inner.iteration.count,
  autostep.count = autostep.count
)

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.
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'.
autostep: Logical, indicating whether the steps should be halved automatically if the new global deviance is greater than the old one. The default is autostep=TRUE.
inner.iteration.count: An integer with the iteration count for the inner iteration.
autostep.count: An integer with the iteration count for the autostep iteration.

Value

A list with the following elements.

dv: Numeric value for the new deviance on the server.
pen: Numeric value with the sum of the quadratic penalties for the parameter.
errorMessage3: String for the validity of the fitted values in the inner iteration. errorMessage3='Fitted values in the inner iteration out of range.' indicates a problem, whereas errorMessage3=NULL means no problem with the fitted values.

Details

It is an aggregation function that updates the distribution parameters and returns the current deviance. The deviance can then be used on the client side to check whether the inner iteration converged. 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