NewPSTR: Create an object of the class PSTR.
In lxylky1688/PSTRM: Panel Smooth Transition Regression Modelling

Description Usage Arguments Details Value Author(s) See Also Examples

Create an object of the S3 class PSTR for later usage. This function should be run prior to the other functions in the package. It will return an object which you will use as an input for the other functions. It builds up the basic settings for the Panel Smooth Transition Regression (PSTR) Modelling.

1	NewPSTR(data, dep, indep, indep_k = NULL, tvars, im = 1, iT)

`data`	a tibble of data. The number of rows of `data` must be the sample size `iT` times individuals number N.
`dep`	column number or name of the dependent variable.
`indep`	a vector of column numbers of names of the independent variables.
`indep_k`	a vector of column numbers of names of the independent variables in the nonlinear part. If `indep_k` is not given (`= NULL`), the nonlinear part will be the same as the linear part.
`tvars`	a vector of column numbers or names of the potential transition variables to be tested.
`im`	maximal number of switches in the transition function used in the linearity evaluation tests, by default `im=1`.
`iT`	sample size.

Potential transition variables in tvars will be tested one by one in, for example, LinTest function.

There is no need to specify the number of individuals, as it will be obtained automatically inside the function given the number of rows and the sample size iT.

NAs in data are removed automatically inside the function.

An object of the class PSTR for later usage.

The object is a list containing the following components:

`iT`	the time length of the panel
`iN`	the number of individuals
`vY`	the vector of the dependent variable
`mX`	the matrix of the explanatory variables in the linear part
`mK`	the matrix of the explanatory variables in the nonlinear part
`mQ`	the matrix of the potential transition variables
`im`	the maximal number of switches used in the linearity test

Yukai Yang, yukai.yang@statistik.uu.se

LinTest

pstr = NewPSTR(Hansen99, dep='inva', indep=4:20, indep_k=c('vala','debta','cfa','sales'),
    tvars=c('vala','debta'), iT=14)

pstr

print(pstr,"summary")