Prepare the clean dataframe for modelling

Usage

clean_data(raw_data, max.ar = 4, max.dl = 2, trend = TRUE)

Arguments

raw_data: A tibble or data.frame with the y variable and the x variables. Needs to have a column called 'time', which is of class Date. Variable names need to be in column 'na_item', and values in column 'values'.
max.ar: Integer. The maximum number of lags to use for the AR terms. as well as for the independent variables.
max.dl: Integer. The maximum number of lags to use for the independent variables (the distributed lags).
trend: Logical. Should a trend be added? Default is TRUE.

Value

A tibble with the cleaned data.

Examples

sample_data <- dplyr::tibble(
  time = rep(seq.Date(
    from = as.Date("2000-01-01"),
    to = as.Date("2000-12-31"), by = 1
  ), each = 2),
  na_item = rep(c("yvar", "xvar"), 366), values = rnorm(366 * 2, mean = 100)
)
osem:::clean_data(sample_data, max.ar = 4, max.dl = 4)
#> # A tibble: 366 × 46
#>    index time       trend  yvar  xvar ln.yvar ln.xvar D.yvar  D.xvar D.ln.yvar
#>    <int> <date>     <dbl> <dbl> <dbl>   <dbl>   <dbl>  <dbl>   <dbl>     <dbl>
#>  1     1 2000-01-01     1  98.4 101.     4.59    4.61 NA     NA       NA      
#>  2     2 2000-01-02     2 102.  101.     4.62    4.61  3.39   0.0845   0.0339 
#>  3     3 2000-01-03     3 101.  100.     4.62    4.61 -0.738 -0.471   -0.00728
#>  4     4 2000-01-04     4  98.9  98.9    4.59    4.59 -2.09  -1.27    -0.0210 
#>  5     5 2000-01-05     5  99.5  99.3    4.60    4.60  0.548  0.462    0.00553
#>  6     6 2000-01-06     6  99.8 102.     4.60    4.62  0.327  2.37     0.00328
#>  7     7 2000-01-07     7  99.0  99.8    4.59    4.60 -0.831 -1.84    -0.00837
#>  8     8 2000-01-08     8 100.   99.0    4.60    4.60  0.987 -0.798    0.00993
#>  9     9 2000-01-09     9 100.  100.     4.61    4.61  0.463  1.07     0.00462
#> 10    10 2000-01-10    10 100.   99.1    4.61    4.60 -0.352 -1.03    -0.00351
#> # ℹ 356 more rows
#> # ℹ 36 more variables: D.ln.xvar <dbl>, L1.yvar <dbl>, L1.xvar <dbl>,
#> #   L1.ln.yvar <dbl>, L1.ln.xvar <dbl>, L1.D.yvar <dbl>, L1.D.xvar <dbl>,
#> #   L1.D.ln.yvar <dbl>, L1.D.ln.xvar <dbl>, L2.yvar <dbl>, L2.xvar <dbl>,
#> #   L2.ln.yvar <dbl>, L2.ln.xvar <dbl>, L2.D.yvar <dbl>, L2.D.xvar <dbl>,
#> #   L2.D.ln.yvar <dbl>, L2.D.ln.xvar <dbl>, L3.yvar <dbl>, L3.xvar <dbl>,
#> #   L3.ln.yvar <dbl>, L3.ln.xvar <dbl>, L3.D.yvar <dbl>, L3.D.xvar <dbl>, …