MomTrunc - Moments of Folded and Doubly Truncated Multivariate Distributions
It computes arbitrary products moments (mean vector and variance-covariance matrix), for some double truncated (and folded) multivariate distributions. These distributions belong to the family of selection elliptical distributions, which includes well known skewed distributions as the unified skew-t distribution (SUT) and its particular cases as the extended skew-t (EST), skew-t (ST) and the symmetric student-t (T) distribution. Analogous normal cases unified skew-normal (SUN), extended skew-normal (ESN), skew-normal (SN), and symmetric normal (N) are also included. Density, probabilities and random deviates are also offered for these members.
Last updated 3 months ago
generation-algorithmsmomentsprobability-statisticsopenblascpp
4.73 score 7 dependents 16 scripts 1.1k downloadsOpportunistic - Routing Distribution, Broadcasts, Transmissions and Receptions in an Opportunistic Network
Computes the routing distribution, the expectation of the number of broadcasts, transmissions and receptions considering an Opportunistic transport model. It provides theoretical results and also estimated values based on Monte Carlo simulations.
Last updated 2 years ago
2.70 score 3 scripts 208 downloadsald - The Asymmetric Laplace Distribution
It provides the density, distribution function, quantile function, random number generator, likelihood function, moments and Maximum Likelihood estimators for a given sample, all this for the three parameter Asymmetric Laplace Distribution defined in Koenker and Machado (1999). This is a special case of the skewed family of distributions available in Galarza et.al. (2017) <doi:10.1002/sta4.140> useful for quantile regression.
Last updated 4 years ago
2.21 score 1 stars 3 dependents 18 scripts 427 downloadslqr - Robust Linear Quantile Regression
It fits a robust linear quantile regression model using a new family of zero-quantile distributions for the error term. Missing values and censored observations can be handled as well. This family of distribution includes skewed versions of the Normal, Student's t, Laplace, Slash and Contaminated Normal distribution. It also performs logistic quantile regression for bounded responses as shown in Galarza et.al.(2020) <doi:10.1007/s13571-020-00231-0>. It provides estimates and full inference. It also provides envelopes plots for assessing the fit and confidences bands when several quantiles are provided simultaneously.
Last updated 7 months ago
2.08 score 1 stars 2 dependents 9 scripts 344 downloadsqrNLMM - Quantile Regression for Nonlinear Mixed-Effects Models
Quantile regression (QR) for Nonlinear Mixed-Effects Models via the asymmetric Laplace distribution (ALD). It uses the Stochastic Approximation of the EM (SAEM) algorithm for deriving exact maximum likelihood estimates and full inference results for the fixed-effects and variance components. It also provides prediction and graphical summaries for assessing the algorithm convergence and fitting results.
Last updated 7 months ago
1.30 score 2 stars 5 scripts 271 downloadsqrLMM - Quantile Regression for Linear Mixed-Effects Models
Quantile regression (QR) for Linear Mixed-Effects Models via the asymmetric Laplace distribution (ALD). It uses the Stochastic Approximation of the EM (SAEM) algorithm for deriving exact maximum likelihood estimates and full inference results for the fixed-effects and variance components. It also provides graphical summaries for assessing the algorithm convergence and fitting results.
Last updated 7 months ago
1.00 score 1 stars 8 scripts 248 downloadsendtoend - Transmissions and Receptions in an End to End Network
Computes the expectation of the number of transmissions and receptions considering an End-to-End transport model with limited number of retransmissions per packet. It provides theoretical results and also estimated values based on Monte Carlo simulations. It is also possible to consider random data and ACK probabilities.
Last updated 6 years ago
1.00 score 2 scripts 164 downloadshopbyhop - Transmissions and Receptions in a Hop by Hop Network
Computes the expectation of the number of transmissions and receptions considering a Hop-by-Hop transport model with limited number of retransmissions per packet. It provides the theoretical results shown in Palma et. al.(2016) <DOI:10.1109/TLA.2016.7555237> and also estimated values based on Monte Carlo simulations. It is also possible to consider random data and ACK probabilities.
Last updated 6 years ago
1.00 score 2 scripts 197 downloads