predict.circ_loess

Compute predictions for circular LOESS

internal

Light-weight functions for computing descriptive statistics in different circular spaces (e.g., 2pi, 180, or 360 degrees), to handle angle-dependent biases, pad circular data, and more. Specifically aimed for psychologists and neuroscientists analyzing circular data. Basic methods are based on Jammalamadaka and SenGupta (2001) <doi:10.1142/4031>, removal of cardinal biases is based on the approach introduced in van Bergen, Ma, Pratte, & Jehee (2015) <doi:10.1038/nn.4150> and Chetverikov and Jehee (2023) <doi:10.1038/s41467-023-43251-w>.

Andrey Chetverikov

circhelp

Circular Analyses Helper Functions

Eline Van Geert

predict.circ_loess function

<dl><dt>object</dt>
<dd>a circular LOESS object</dd>
<dt>newdata</dt>
<dd>a data.frame with a variable x on which the predictions are computed</dd>
<dt>...</dt>
<dd>other arguments (passed to circ_loess)</dd></dl>

Arguments

Compute predictions for circular LOESS — predict.circ_loess

<dl>

<dt>object</dt>
<dd>a circular LOESS object</dd>


<dt>newdata</dt>
<dd>a data.frame with a variable x on which the predictions are computed</dd>


<dt>...</dt>
<dd>other arguments (passed to circ_loess)</dd>

</dl>

predict.circ_loess: Compute predictions for circular LOESS

Description

Usage

Value

Arguments