likelihood-functions

There are 0 repository under likelihood-functions topic.

• JuliaGaussianProcesses / GPLikelihoods.jl

  Provides likelihood functions for Gaussian Processes.

  gaussian-processeslikelihoodlikelihood-functions
  Language:Julia 43

• xpsi-group / xpsi

  X-PSI: X-ray Pulse Simulation and Inference

  astrophysicsastronomyastronomical-algorithmsastrophysical-simulationsamplingparameter-estimationstatistics-modelingmodelinglikelihood-functionsposterior-samplingx-ray-astronomy
  Language:Python 34

• LSSTDESC / firecrown

  DESC Cosmology Likelihood Framework

  cobayacosmosislikelihood-functionspythonsamplernumcosmo
  Language:Python 29

• JuBiotech / calibr8

  Toolbox for non-linear calibration modeling.

  bayesian-inferencecalibrationcalibration-curvelikelihood-functionspymc
  Language:Jupyter Notebook 24
• concurve

  zadrafi / concurve

  A repository for the 'concurve' R package which generates confidence distributions and likelihood functions. Includes documentation on how to do produce similar graphs for Stata.

  confidence-intervalscompatibility-intervalsstataconfidence-distributionlikelihood-functionsbootstrap-methodrfrequentist-methodsfiducial-distributionconsonancedensity-functioncumulative-distribution-functionsurprisal-functiondeviance-function
  Language:TeX 20

• lbelzile / mev

  Modelling extreme values

  extreme-value-statisticsthreshold-selectionmax-stablesimulationlikelihood-functions
  Language:R 12

• rplzzz / mcpar

  Parallel Metropolis-Hastings Markov chain Monte Carlo toolkit

  markov-chainlikelihood-functionsmetropolismpimonte-carloparallelquasi-ergodicity-problem
  Language:C++ 4

• austinschneider / MCLLH

  Likelihood to account for Monte Carlo statistical uncertainties

  physics-analysisstatisticspoissonlikelihoodlikelihood-functionsphysics
  Language:CSS 2

• bcbi / MaximumLikelihoodProblems.jl

  Formulate likelihood problems and solve them with maximum likelihood estimation (MLE)

  maximum-likelihoodmaximum-likelihood-problemsmaximum-likelihood-estimationlikelihoodlikelihood-functionslog-likelihoodlog-likelihood-functionsstatisticsstatistical-inference
  Language:Julia 1

• ameli / detkit

  Matrix Determinant Toolkit

  matrix-functionsmatrix-computationsgaussian-processeslikelihood-functionsposterior-probabilitymachine-learning
  Language:Python 0

• Scrayil / GlobClus_prop-Analysis

  This aim of this project is to analyze globular star clusters in the Milky Way, in order to understand their dynamics. The conducted study examined the properties that affect the central velocity dispersion, their impact and the correlations between them.

  aicastrophysicsbayesian-networksbicconfidence-intervalscorrelation-analysisgaussian-distributiongaussian-graphical-modelsglobular-clusterslikelihood-functionslinear-modelsp-valuerspacestarsstatistical-analysisstatistical-learningstatisticsuniversereport
  Language:HTML 0

• ashishyadav24092000 / MaximumLikelihoodEstimator

  The maximum likelihoood estimator approach is used here for calculating the Regression parameter that is slope(b1),intercept(b0) and standard deviation of error/residuals. Then Result or the output for the regression parameters using the OLS(ordiniary Least Sqaure) estimation method versus the MLE(MAximum Likelihood Estimation) method is compared. Also note that this MLE is used when the residual(e) of the regression model does not follow normal distribution for different observations.

  mle-estimationlikelihood-functionsregressionnormaldistribution
  Language:Jupyter Notebook

• ashishyadav24092000 / MAximumLIkelihoodEstimator2_TVads_and_carsold

  Here for a small dataset we have used OLS(Ordiniary Least Square) and MLE(Maximum likelihood Estimation ) to calculate the regression parameters slope(b1),intercept(b0) and standard deviation of reisduals.At the end we can conclude that both the methods of estimation produces the same result.

  mle-estimationlikelihood-functionsregressionols-regressionscatter-plotmaximum-likelihood-estimation
  Language:Jupyter Notebook

• PeterSchuld / TUe-Improving_Statistical_Inferences

  Eindhoven University of Technology (TU/e) course "Improving your statistical inferences" by Daniel Lakens on Coursera (completed Dec 2022).

  bayesian-statisticslikelihood-functionsp-valuesstatistical-inference
  Language:R

• queelius / dfr_dist

  Dynamic failure rate distributions (DFR)

  autoregressivefailure-ratelikelihood-functionsmaximum-likelihood-estimationreliabilitystatistical-inferencesurvival-analysis
  Language:R