fquantile

This function is a faster implementation of the "type 7" <code><a href="/link/quantile()?package=logitr&version=1.1.2" data-mini-rdoc="logitr::quantile()">quantile()</a></code>
algorithm and is modified from this gist:
https://gist.github.com/sikli/f1775feb9736073cefee97ec81f6b193
It returns sample quantiles corresponding to the given probabilities.
The smallest observation corresponds to a probability of 0 and the largest
to a probability of 1. For speed, output quantile names are removed as are
error handling such as checking if x are factors, or if probs lie outside
the <code>[0,1]</code> range.

Fast estimation of multinomial (MNL) and mixed logit (MXL) models in R. Models can be estimated using "Preference" space or "Willingness-to-pay" (WTP) space utility parameterizations. Weighted models can also be estimated. An option is available to run a parallelized multistart optimization loop with random starting points in each iteration, which is useful for non-convex problems like MXL models or models with WTP space utility parameterizations. The main optimization loop uses the 'nloptr' package to minimize the negative log-likelihood function. Additional functions are available for computing and comparing WTP from both preference space and WTP space models and for predicting expected choices and choice probabilities for sets of alternatives based on an estimated model. Mixed logit models can include uncorrelated or correlated heterogeneity covariances and are estimated using maximum simulated likelihood based on the algorithms in Train (2009) <doi:10.1017/CBO9780511805271>. More details can be found in Helveston (2023) <doi:10.18637/jss.v105.i10>.

John Helveston

logitr

Logit Models w/Preference & WTP Space Utility Parameterizations

Connor Forsythe

fquantile function

<dl><dt>x</dt>
<dd>numeric vector whose sample quantiles are wanted. <code>NA</code> and <code>NaN</code>
values are not allowed in numeric vectors unless <code>na.rm</code> is <code>TRUE</code>.</dd>
<dt>probs</dt>
<dd>numeric vector of probabilities with values in <code>[0,1]</code>.
(Values up to <code>2e-14</code> outside that range are accepted and moved to the
nearby endpoint.)</dd>
<dt>na.rm</dt>
<dd>logical; if <code>TRUE</code>, any <code>NA</code> and <code>NaN</code>'s are removed from <code>x</code>
before the quantiles are computed.</dd></dl>

Arguments

This function is a faster implementation of the "type 7" <code><a href='https://rdrr.io/r/stats/quantile.html'>quantile()</a></code>
algorithm and is modified from this gist:
https://gist.github.com/sikli/f1775feb9736073cefee97ec81f6b193
It returns sample quantiles corresponding to the given probabilities.
The smallest observation corresponds to a probability of 0 and the largest
to a probability of 1. For speed, output quantile names are removed as are
error handling such as checking if x are factors, or if probs lie outside
the <code>[0,1]</code> range.

Predict probabilities and / or outcomes — fquantile

<dl>

<dt>x</dt>
<dd>numeric vector whose sample quantiles are wanted. <code>NA</code> and <code>NaN</code>
values are not allowed in numeric vectors unless <code>na.rm</code> is <code>TRUE</code>.</dd>


<dt>probs</dt>
<dd>numeric vector of probabilities with values in <code>[0,1]</code>.
(Values up to <code>2e-14</code> outside that range are accepted and moved to the
nearby endpoint.)</dd>


<dt>na.rm</dt>
<dd>logical; if <code>TRUE</code>, any <code>NA</code> and <code>NaN</code>'s are removed from <code>x</code>
before the quantiles are computed.</dd>

</dl>

fquantile: Predict probabilities and / or outcomes

Description

Usage

Value

Arguments

Examples