If you reallllllllly want to....

It's kind of annoying that most `forecast`

package functions are not generics. This makes it difficult for us to extend the package to data.frames and other new objects.

```
library(tibbletime)
library(dplyr)
library(forecast)
# as.ts() is generic, let's go ahead and make a tbl_time method
as.ts.tbl_time <- function(x, ...) {
index_quo <- tibbletime::get_index_quo(x)
index_col <- tibbletime::get_index_col(x)
x_no_index <- dplyr::select(x, - !! index_quo)
start <- dplyr::first(index_col)
end <- dplyr::last(index_col)
ts(data = x_no_index, start = start, end = end, ...)
}
# Every forecast package function is not a generic for some reason :(
# Force it to be one anyways for the sake of the example
ets <- function(y, model = "ZZZ", damped = NULL, alpha = NULL, beta = NULL,
gamma = NULL, phi = NULL, additive.only = FALSE, lambda = NULL,
biasadj = FALSE, lower = c(rep(1e-04, 3), 0.8), upper = c(rep(0.9999, 3), 0.98),
opt.crit = c("lik", "amse", "mse", "sigma", "mae"), nmse = 3,
bounds = c("both", "usual", "admissible"), ic = c("aicc", "aic", "bic"),
restrict = TRUE, allow.multiplicative.trend = FALSE,
use.initial.values = FALSE, ...) {
UseMethod("ets")
}
# The default just calls the forecast version directly
ets.default <- function(y, model = "ZZZ", damped = NULL, alpha = NULL, beta = NULL,
gamma = NULL, phi = NULL, additive.only = FALSE, lambda = NULL,
biasadj = FALSE, lower = c(rep(1e-04, 3), 0.8), upper = c(rep(0.9999, 3), 0.98),
opt.crit = c("lik", "amse", "mse", "sigma", "mae"), nmse = 3,
bounds = c("both", "usual", "admissible"), ic = c("aicc", "aic", "bic"),
restrict = TRUE, allow.multiplicative.trend = FALSE,
use.initial.values = FALSE, ...) {
forecast::ets(y, model = "ZZZ", damped = NULL, alpha = NULL, beta = NULL,
gamma = NULL, phi = NULL, additive.only = FALSE, lambda = NULL,
biasadj = FALSE, lower = c(rep(1e-04, 3), 0.8), upper = c(rep(0.9999, 3), 0.98),
opt.crit = c("lik", "amse", "mse", "sigma", "mae"), nmse = 3,
bounds = c("both", "usual", "admissible"), ic = c("aicc", "aic", "bic"),
restrict = TRUE, allow.multiplicative.trend = FALSE,
use.initial.values = FALSE, ...)
}
# The method for tbl_time first coerces to ts
ets.tbl_time <- function(y, model = "ZZZ", damped = NULL, alpha = NULL, beta = NULL,
gamma = NULL, phi = NULL, additive.only = FALSE, lambda = NULL,
biasadj = FALSE, lower = c(rep(1e-04, 3), 0.8), upper = c(rep(0.9999, 3), 0.98),
opt.crit = c("lik", "amse", "mse", "sigma", "mae"), nmse = 3,
bounds = c("both", "usual", "admissible"), ic = c("aicc", "aic", "bic"),
restrict = TRUE, allow.multiplicative.trend = FALSE,
use.initial.values = FALSE, ...) {
# Pass ... to as.ts() so you can control frequency
# May or may not work / be useful
y <- as.ts(y, ...)
forecast::ets(y, model = "ZZZ", damped = NULL, alpha = NULL, beta = NULL,
gamma = NULL, phi = NULL, additive.only = FALSE, lambda = NULL,
biasadj = FALSE, lower = c(rep(1e-04, 3), 0.8), upper = c(rep(0.9999, 3), 0.98),
opt.crit = c("lik", "amse", "mse", "sigma", "mae"), nmse = 3,
bounds = c("both", "usual", "admissible"), ic = c("aicc", "aic", "bic"),
restrict = TRUE, allow.multiplicative.trend = FALSE,
use.initial.values = FALSE)
}
# Let's try it out
data(FB)
FB %>%
select(date, adjusted) %>%
as_tbl_time(date) %>%
ets()
#> ETS(M,A,N)
#>
#> Call:
#> forecast::ets(y = y, model = "ZZZ", damped = NULL, alpha = NULL,
#>
#> Call:
#> beta = NULL, gamma = NULL, phi = NULL, additive.only = FALSE,
#>
#> Call:
#> lambda = NULL, biasadj = FALSE, lower = c(rep(1e-04, 3),
#>
#> Call:
#> 0.8), upper = c(rep(0.9999, 3), 0.98), opt.crit = c("lik",
#>
#> Call:
#> "amse", "mse", "sigma", "mae"), nmse = 3, bounds = c("both",
#>
#> Call:
#> "usual", "admissible"), ic = c("aicc", "aic", "bic"),
#>
#> Call:
#> restrict = TRUE, allow.multiplicative.trend = FALSE, use.initial.values = FALSE)
#>
#> Smoothing parameters:
#> alpha = 0.9999
#> beta = 1e-04
#>
#> Initial states:
#> l = 28.0112
#> b = 0.0932
#>
#> sigma: 0.0307
#>
#> AIC AICc BIC
#> 12491.56 12491.60 12517.99
```

Created on 2018-01-18 by the reprex package (v0.1.1.9000).