The function mc_ma helps to build the components
of the matrix linear predictor associated with moving average models.
This function is generaly used for the analysis of longitudinal and
times series data. The user can specify the order of the moving
average process.
mc_ma(id, time, data, order = 1)
| id | name of the column (string) containing the subject index.
Note that this structure was designed to deal with longitudinal data.
For times series data use the same |
|---|---|
| time | name of the column (string) containing the index indicating the time. |
| data | data set. |
| order | order of the moving average process. |
Bonat, W. H. (2018). Multiple Response Variables Regression Models in R: The mcglm Package. Journal of Statistical Software, 84(4):1--30.
A matrix of dgCMatrix class.
This function was designed mainly to deal with longitudinal
data, but can also be used for times series analysis. In that case,
the id argument should contain only one index. It pretends a
longitudinal data taken just for one individual or unit sample. This
function is a simple call of the bandSparse
function from the Matrix package.
mc_id, mc_dist, mc_car,
mc_rw and mc_mixed.
id <- rep(1:2, each = 4) time <- rep(1:4, 2) data <- data.frame("id" = id, "time" = time) mc_ma(id = "id", time = "time", data = data, order = 1)#> $Z1 #> 8 x 8 sparse Matrix of class "nsCMatrix" #> #> [1,] . | . . . . . . #> [2,] | . | . . . . . #> [3,] . | . | . . . . #> [4,] . . | . . . . . #> [5,] . . . . . | . . #> [6,] . . . . | . | . #> [7,] . . . . . | . | #> [8,] . . . . . . | . #>mc_ma(id = "id", time = "time", data = data, order = 2)#> $Z1 #> 8 x 8 sparse Matrix of class "nsCMatrix" #> #> [1,] . . | . . . . . #> [2,] . . . | . . . . #> [3,] | . . . . . . . #> [4,] . | . . . . . . #> [5,] . . . . . . | . #> [6,] . . . . . . . | #> [7,] . . . . | . . . #> [8,] . . . . . | . . #>