Calculate a synthetic time series using a penalized regression and a donor pool.
SCUL(
PostPeriodLength = nrow(SCUL.input$y) - SCUL.input$TreatmentBeginsAt + 1,
PrePeriodLength = SCUL.input$TreatmentBeginsAt - 1,
NumberInitialTimePeriods = SCUL.input$NumberInitialTimePeriods,
OutputFilePath = SCUL.input$OutputFilePath,
x.DonorPool.PreTreatment = SCUL.input$x.DonorPool.PreTreatment,
y.PreTreatment = SCUL.input$y.PreTreatment,
x.DonorPool = SCUL.input$x.DonorPool,
time = SCUL.input$time,
y.actual = SCUL.input$y,
TreatmentBeginsAt = SCUL.input$TreatmentBeginsAt,
TrainingPostPeriodLength = SCUL.input$TrainingPostPeriodLength,
cvOption = "lambda.1se",
plotCV = FALSE
)| PostPeriodLength | An integer that indicates the length of the post-treatment period. Defailt is calculated using SCUL.input data. |
|---|---|
| PrePeriodLength | An integer that indicates the length of the pre-treatment period. Defailt is calculated using SCUL.input data. |
| NumberInitialTimePeriods | An integer that indicates the number of time periods desired in the training data for the first cross-validation run. Default is the stated amount in SCUL.input data. |
| OutputFilePath | A file path to store output. Default is taken from SCUL.input$OutputFilePath |
| x.DonorPool.PreTreatment | A data frame with the pre-treament values of the donor pool. Default is to extract this from SCUL.input$x.DonorPool.PreTreatment |
| y.PreTreatment | A data frame with the pre-treament values of the target variable Default is to extract this from SCUL.input$y.PreTreatment |
| x.DonorPool | A data frame with the all values of the donor pool. Default is to extract this from SCUL.input$x.DonorPool |
| time | A data frame that is a column vector (Tx1) sorted by time. Default is taken from SCUL.input$time |
| y.actual | A data frame that is a column vector (Tx1) sorted by time Default is taken from SCUL.input$y |
| TreatmentBeginsAt | An integer indicating which row begins treatment. Default is to begin this at SCUL.input$TreatmentBeginsAt. |
| TrainingPostPeriodLength | The number of timer periods post-treatment for training data. Defaults to all time since treatment begins. |
| cvOption | Do you want to use the median CV lambda (cvOption = lambda.median), one that produces the minimum MSE (cvOption = lambda.min), or the largest lambda that produces a MSE within one standard error of the minimum MSE (cvOption = lambda.1se). Default is lambda.1se |
| plotCV | Create a plot of the cross-validated mean squared error against -log(lambda) of the penalty parameter. Default is to not plot CV curve (plotCV == FALSE). |
OutputDataSCUL A list with the synthetic series, weights used to construct the series, and measures of fit.