Packaged: 2022-04-24 17:55:15 UTC; francescobartolucci

Title: Filter Methods for Parameter Estimation in Linear Regression
person("Christian", "Llano Robayo", email = "cxl985@miami.edu", role = c("aut","cre")),
person("Nazrul", "Shaikh", email = "n.shaikh@miami.edu", role = "aut")
Description: We present a method based on filtering algorithms to estimate the parameters of linear regressions, i.e. the coefficients and the variance of the error term. The proposed algorithm makes use of Particle Filters following Ristic, B., Arulampalam, S., Gordon, N. (2004, ISBN: 158053631X) resampling methods.
Author: Christian Llano Robayo [aut, cre],
Maintainer: Christian Llano Robayo <cxl985@miami.edu>

Description: We present a method based on filtering algorithms to estimate the parameters of linear regressions, i.e. the coefficients and the variance of the error term. The proposed algorithms make use of Particle Filters following Ristic, B., Arulampalam, S., Gordon, N. (2004, ISBN: 158053631X) resampling methods.
Packaged: 2018-08-14 03:56:04 UTC; luiscastroabril

Title: Filter Methods for Parameter Estimation in Linear and Non Linear
person("Nazrul", "Shaikh", email = "nazrul@cecareus.com", role = "aut")
Description: We present a method based on filtering algorithms to estimate the parameters of linear, i.e. the coefficients and the variance of the error term. The proposed algorithms make use of Particle Filters following Ristic, B., Arulampalam, S., Gordon, N. (2004, ISBN: 158053631X) resampling methods. Parameters of logistic regression models are also estimated using an evolutionary particle filter method.

Title: Advanced L-Moment Fitting of Distributions
Description: A complete framework for frequency analysis is provided by 'LMoFit'. It has functions related to the determination of sample L-moments as in Hosking, J.R.M. (1990) <doi:10.1111/j.2517-6161.1990.tb01775.x>, the fitting of various distributions as in Zaghloul et al. (2020) <doi:10.1016/j.advwatres.2020.103720> and Hosking, J.R.M. (2019) <https://CRAN.R-project.org/package=lmom>, besides plotting and manipulating L-space diagrams as in Papalexiou, S.M. & Koutsoyiannis, D. (2016) <doi:10.1016/j.advwatres.2016.05.005> for two-shape parametric distributions on the L-moment ratio diagram. Additionally, the quantile, probability density, and cumulative probability functions of various distributions are provided in a user-friendly manner.
Imports: lmom, pracma, stats, ggplot2, sf, utils