dssLmResid: Calculate residuals for a linear regression

In sib-swiss/dsSwissKnifeClient: DataSHIELD Tools and Utilities - client side

Calculate residuals for a linear regression

Description

Create a dataframe on the remote node(s) containing the residuals for one or more linear regression models. The models can be local to the respective nodes (resulted from a call to lm()) or global (resulted from a call to ds.glm). The choice between the 2 behaviours is dictated by the nature of the first argument, see below

Usage

dssLmResid(
  outcomes,
  indvars,
  data,
  newobj = "residuals",
  async = TRUE,
  datasources = NULL
)

Arguments

outcomes	can be a vector of column names or a named list. If it is a vector, a local linear model (lm()) will be created on the remote servers for each of its members using the variables in 'indvars' as predictors. If it is a named list, the names must be again column names and the elements must be vectors of coefficients (starting with the intercept , the same structure as lm()$coefficients or ds.glm()$coefficients). In this case the residuals will be directly calculated on each node. Only simple models are supported without interactions (ex: Petal.Length ~ Sepal.Length + Sepal.Width + Petal.Width)
indvars	a vector of column names, the predictors used for all models. A name can be present both here and in outcomes, if this is the case it will be eliminated from the predictors when needed.
data	the name of the data frame containing the columns.
newobj	the name of the new data frame containing the residuals. The column names of this data frame will be the column names in 'outcomes'
async	a logical, see datashield.aggregate
datasources	a list of opal objects obtained after logging into the opal servers (see datashield.login)

sib-swiss/dsSwissKnifeClient documentation built on July 16, 2025, 6:25 p.m.