BETS.corrgram: Plot the ACF or the PACF of a time series
In pedrocostaferreira/BETS: Brazilian Economic Time Series

Plot correlograms using plot.ly and several other options that differ theses plots from forecasts ACF and PACF.

1 2	BETS.corrgram(ts, lag.max = 12, type = "correlation", mode = "simple", ci = 0.95, style = "plotly", knit = F)

`ts`	An object of type `ts` or `xts`. The time series for which the plot must be constructed.
`lag.max`	A `numeric` value. The number of lags to be shown in the plot.
`type`	A `character`. Can be either 'correlation' (for the ACF) or 'partial' (for the PACF).
`mode`	A `character`. Set this parameter to 'bartlett' if you want the variance to be calculated according to Bartlett's formula. Otherwise, it is going to be simply equal to `1/sqrt(N)`.
`ci`	A `numeric` value. The confidence interval to be shown in the plot.
`style`	A `character`. Set this parameter to 'normal' if you want it made with ggplot2 or to 'plotly' if you want to be a plotly object.
`knit`	A `boolean`. If you're using this function to exhibit correlograms on a R dynamic report, set this parameter to true.