I'm trying to do predict using multiple linear regression in R. I have been able to do the multiple regression bit, by converting raw data to data table. However, when i'm trying to use predict function, i'm unable to do it at multiple variable level, for each SKU ... as given below.   

    SKU	Sales	Week	AP	Discount
    101451	1308	2010_19	3.48	0.1
    101451	1678	2010_20	3.5	0
    101451	2003	2010_21	3.5	0.12
    495172	168	2012_18	5.36	0
    495172	138	2012_19	5.15	0
    495172	97	2012_20	4.99	0
    495172	377	2012_21	3.5	0.26
    586606	130	2012_7	7.24	0
    586606	143	2012_8	6.46	0.07
    586606	1098	2012_9	4.99	0.28

The code I have used is (mlr is the rawdata)

    library(data.table)
    mlrt<- data.table(SKU=mlr$SKU,Sales=mlr$Sales,Week=mlr$Week,AP=mlr$AP,Discount=mlr$Discount)

    # Run MLR model, by SKU,Display multiple Intercepts and slopes, SKU wise
    mlrt[,list(intercept=coef(lm(Sales~AP+Discount))   [1],SLOPE1=coef(lm(Sales~AP+Discount))[2],SLOPE2=coef(lm(Sales~AP+Discount))[3]),by=SKU]

I'm unable to figure out how to predict using `predict` function here, for each `SKU` separately. (`Sales` is DV and `AP` and `Discount` are IDV)