Model Correlated data Interactively build a model of correlated data

Model Correlated data Interactively build a model of correlated data

model_cor(xs, parallel = FALSE, cl = NULL)

Arguments

xs	the time series to model
parallel	whether or not to run in parallel, defaults to FALSE
cl	the cluster in which to run on

Value

a list of model metrics and paramaters

Examples

xs <- playground(400)
clust <- parallel::makeCluster(2L, type = "FORK")
#> Error in makeForkCluster(nnodes = spec, ...): fork clusters are not supported on Windows
model_cor(xs, parallel = TRUE, cl = clust)
#> 
#> Coefficients of Original polynomial:  
#> 0.5125 -0.2984 0.1591 -0.2294 0.0329 -0.0213 0.0337 -0.0589 -0.1197 0.0611 0.0527 -0.0540 0.0405 -0.0470 0.1299 0.0429 -0.0325 0.0693 0.0331 -0.0236 
#> 
#> Factor                 Roots                Abs Recip    System Freq 
#> 1-1.7186B+0.8717B^2    0.9857+-0.4189i      0.9337       0.0640
#> 1+0.2158B+0.8544B^2   -0.1263+-1.0744i      0.9244       0.2686
#> 1+1.3304B+0.8403B^2   -0.7916+-0.7506i      0.9167       0.3792
#> 1+0.7498B+0.8107B^2   -0.4624+-1.0097i      0.9004       0.3184
#> 1-0.8997B              1.1114               0.8997       0.0000
#> 1-1.3072B+0.7881B^2    0.8294+-0.7623i      0.8877       0.1183
#> 1-0.8384B+0.7397B^2    0.5668+-1.0152i      0.8601       0.1690
#> 1-0.5364B+0.6966B^2    0.3850+-1.1346i      0.8346       0.1979
#> 1+1.5113B+0.6088B^2   -1.2412+-0.3194i      0.7803       0.4599
#> 1+1.3710B+0.5354B^2   -1.2804+-0.4780i      0.7317       0.4431
#> 1-0.3905B              2.5610               0.3905       0.0000
#>   
#>   
#> enter an arima order: 
#> Error in if (d_order > 0) {    res <- difference("arima", xs, d_order)    return(list(d = d_order, result = res))} else {    res <- xs    return(list(d = d_order, result = res))}: missing value where TRUE/FALSE needed