Null hypothesis: data follows a time series model using auto.arima from the forecast package
null_ts(var, modelfn)
var | variable to model as a time series |
---|---|
modelfn | method for simulating from ts model. |
... | other arguments passed onto |
a function that given data
generates a null data set.
For use with lineup
or rorschach
null_model
require(forecast)#>#>ggplot(l, aes(x=date, y=rate)) + geom_line() + facet_wrap(~.sample, scales="free_y") + theme(axis.text = element_blank()) + xlab("") + ylab("")l_dif <- l %>% group_by(.sample) %>% mutate(d=c(NA,diff(rate))) %>% ggplot(aes(x=d)) + geom_density() + facet_wrap(~.sample)