check_fitQ_args: Check and validate arguments for fitQ()
In pnnl/qFeature: Extract Features from Continuous or Discrete Time Series

Description Usage Arguments Details Value Author(s)

Check and validate arguments for fitQ before they are used.

1 2	check_fitQ_args(x1 = -10:10, min.window = 5, start = 1, skip = 1, linear.only = FALSE)

`x1`	The predictor of the regression model, whose length must be odd, and it must be monotonic (increasing or decreasing). Typically this would be an evenly spaced, increasing vector.
`min.window`	The minimum number of non-missing data points in a window that are required to fit the regression model.
`start`	The index of the center of the first window
`skip`	The number of indexes to advance the center of the moving window each time the model is fit.
`linear.only`	`=TRUE` fits a simple linear regression model with `x1` as the single predictor, instead of a quadratic regression model.

This function exists so that multiple calls to fitQ from getFeatures would not involve repeating the checks on essentially the same arguments.

An object of class valid_fitQ_args that can be passed to the x1 argument of fitQ. It is a list with the same elements that were passed into the function: x1, min.window, start, skip, linear.only, plus one more, the bandwidth (bw), which is equal to (length(x1) - 1) / 2.