Logistic_Density

Computes the function:
$$g(\theta; \tau) = \displaystyle \frac{\exp\left(-\frac{\theta}{\tau}\right)}{\tau \left(1 + \exp\left(-\frac{\theta}{\tau}\right)\right)^2}$$

internal

Implements methods for calibrating an aggregated functional data model using
wavelets or splines. Each aggregated curve is modeled as a linear combination of
component functions and known weights. The component functions are estimated using
wavelets or splines. The package is based on dos Santos Sousa (2024) <doi:10.1515/mcma-2023-2016>
and Saraiva and Dias (2009) <doi:10.47749/T/UNICAMP.2009.471073>.

Vitor Perrone

FunctionalCalibration

Aggregated Functional Data Calibration using Splines and
Wavelets

Alex Sousa

Logistic_Density function

<dl><dt>theta</dt>
<dd>Numeric value of $\theta$.</dd>
<dt>tau</dt>
<dd>Numeric value of $\tau$.</dd></dl>

Arguments

Logistic Density — Logistic_Density

<dl>

<dt>theta</dt>
<dd>Numeric value of $\theta$.</dd>


<dt>tau</dt>
<dd>Numeric value of $\tau$.</dd>

</dl>

Logistic_Density: Logistic Density

Description

Usage

Value

Arguments