update_BLP_data {BLPestimatoR}

Updates the set of linear, exogenous, random coefficient, share or mean utility variable in the data object.

Description

Updates the set of linear, exogenous, random coefficient, share or mean utility variable in the data object.

Usage

update_BLP_data(data_update, blp_data)

Arguments

data_update

data.frame with variables to update (must contain the market_identifier and product_identifier variables as in blp_data),

blp_data

data object created by the function BLP_data

Value

Returns an object of class blp_data.

Examples

K<-2 #number of random coefficients
data <- simulate_BLP_dataset(nmkt = 25, nbrn = 20,
                        Xlin = c("price", "x1", "x2", "x3", "x4", "x5"),
                        Xexo = c("x1", "x2", "x3", "x4", "x5"),
                        Xrandom = paste0("x",1:K),instruments = paste0("iv",1:10),
                        true.parameters = list(Xlin.true.except.price = rep(0.2,5),
                                               Xlin.true.price = -0.2,
                                               Xrandom.true = rep(2,K),
                                               instrument.effects = rep(2,10),
                                               instrument.Xexo.effects = rep(1,5)),
                        price.endogeneity = list( mean.xi = -2,
                                                  mean.eita = 0,
                                                  cov = cbind( c(1,0.7), c(0.7,1))),
                        printlevel = 0, seed = 234234 )


model <- as.formula("shares ~  price + x1 + x2 + x3 + x4 + x5 |
                    x1 + x2 + x3 + x4 + x5 |
                    0+ x1 + x2 |
                    iv1 + iv2 + iv3 + iv4 + iv5 + iv6 + iv7 + iv8 +iv9 +iv10" )

blp_data <- BLP_data(model = model, market_identifier="cdid",
                     product_id = "prod_id",
                     productData = data,
                     integration_method = "MLHS" ,
                     integration_accuracy = 40,
                     integration_seed = 1)

new_data <- data.frame(price = seq(1,10,length.out=500),
                       x1 =  seq(2,10,length.out=500),
                       cdid = sort(rep(1:25,20)),
                       prod_id = rep(1:20,25) )
blp_data_example_updated <-update_BLP_data(blp_data = blp_data,
                                           data_update = new_data)