Computes the standard errors and confidence intervals on the beta (i.e., working) scale of the data stream probability distribution parameters,
as well as for the transition probabilities regression parameters. Working scale depends on the real (i.e., natural) scale of the parameters. For
non-circular distributions or for circular distributions with
CIbeta(m, alpha = 0.95)
Significance level of the confidence intervals. Default: 0.95 (i.e. 95% CIs).
1) if both lower and upper bounds are finite then logit is the working scale; 2) if lower bound is finite and upper bound is infinite then log is the working scale.
For circular distributions with
estAngleMean=TRUE and no constraints imposed by a design matrix (DM) or bounds (userBounds), then the working parameters
are complex functions of both the angle mean and concentrations/sd natural parameters (in this case, it's probably best just to focus on the real parameter
estimates!). However, if constraints are imposed by DM or userBounds on circular distribution parameters with
1) if the natural bounds are (-pi,pi] then tangent is the working scale, otherwise if both lower and upper bounds are finite then logit is the working scale; 2) if lower bound is finite and upper bound is infinite then log is the working scale.
When circular-circular regression is specified using
circularAngleMean, the working scale
for the mean turning angle is not as easily interpretable, but the
link function is atan2(sin(X)*B,1+cos(X)*B), where X are the angle covariates and B the angle coefficients.
Under this formulation, the reference turning angle is 0 (i.e., movement in the same direction as the previous time step).
In other words, the mean turning angle is zero when the coefficient(s) B=0.
A list of the following objects:
List(s) of estimates ('est'), standard errors ('se'), and confidence intervals ('lower', 'upper') for the working parameters of the data streams
List of estimates ('est'), standard errors ('se'), and confidence intervals ('lower', 'upper') for the working parameters of the transition probabilities
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