gradLK: Create gradient function approximation via PRACMA package
In gabrielfranco89/aggrmodel: A R package to fit aggregated data model

Create gradient function approximation via PRACMA package

gradLK(
  x,
  dataWrap,
  mktWrap,
  sCovWrap,
  covWrap,
  corWrap,
  betaWrap,
  designWrap,
  nCons,
  nBasisCov,
  nOrderCov,
  verbWrap,
  positive = FALSE,
  truncateDec = NULL
)

`x`	parameters to be evaluated
`dataWrap`	dataset
`mktWrap`	market dataset
`sCovWrap`	Sample covariance matrix
`covWrap`	covariance structure
`corWrap`	correlation structure
`betaWrap`	beta parameter
`designWrap`	Design matrix
`nCons`	number of types of consumers
`nBasisCov`	number of basis functions for functional variance
`nOrderCov`	order of basis functions for functional variance
`verbWrap`	TRUE/FALSE prints likelihood values during optimization
`positive`	Use positive restriction?
`truncateDec`	Integer: Decimal to be truncated in exponential functional