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  • Installing
  • Getting started
  • User Guide
  • Examples
  • API Reference
  • About statsmodels
  • Developer Page
  • Release Notes
  • GitHub
  • PyPI
  • DOI

Section Navigation

  • endog, exog, what’s that?
  • Import Paths and Structure
  • Fitting models using R-style formulas
  • Pitfalls
  • Linear Regression
  • Generalized Linear Models
  • Generalized Estimating Equations
  • Generalized Additive Models (GAM)
  • Robust Linear Models
  • Linear Mixed Effects Models
  • Regression with Discrete Dependent Variable
  • Generalized Linear Mixed Effects Models
  • ANOVA
  • Other Models othermod
  • Time Series analysis tsa
  • Time Series Analysis by State Space Methods statespace
  • Vector Autoregressions tsa.vector_ar
  • Methods for Survival and Duration Analysis
  • Nonparametric Methods nonparametric
    • statsmodels.nonparametric.smoothers_lowess.lowess
    • statsmodels.nonparametric.kde.KDEUnivariate
    • statsmodels.nonparametric.kernel_density.KDEMultivariate
    • statsmodels.nonparametric.kernel_density.KDEMultivariateConditional
    • statsmodels.nonparametric.kernel_density.EstimatorSettings
    • statsmodels.nonparametric.kernel_regression.KernelReg
      • statsmodels.nonparametric.kernel_regression.KernelReg.aic_hurvich
      • statsmodels.nonparametric.kernel_regression.KernelReg.cv_loo
      • statsmodels.nonparametric.kernel_regression.KernelReg.fit
      • statsmodels.nonparametric.kernel_regression.KernelReg.loo_likelihood
      • statsmodels.nonparametric.kernel_regression.KernelReg.r_squared
      • statsmodels.nonparametric.kernel_regression.KernelReg.sig_test
    • statsmodels.nonparametric.kernel_regression.KernelCensoredReg
    • statsmodels.nonparametric.bandwidths.bw_scott
    • statsmodels.nonparametric.bandwidths.bw_silverman
    • statsmodels.nonparametric.bandwidths.select_bandwidth
    • statsmodels.nonparametric.kernels_asymmetric.pdf_kernel_asym
    • statsmodels.nonparametric.kernels_asymmetric.cdf_kernel_asym
    • statsmodels.nonparametric.kernels_asymmetric.kernel_pdf_beta
    • statsmodels.nonparametric.kernels_asymmetric.kernel_pdf_beta2
    • statsmodels.nonparametric.kernels_asymmetric.kernel_pdf_bs
    • statsmodels.nonparametric.kernels_asymmetric.kernel_pdf_gamma
    • statsmodels.nonparametric.kernels_asymmetric.kernel_pdf_gamma2
    • statsmodels.nonparametric.kernels_asymmetric.kernel_pdf_invgamma
    • statsmodels.nonparametric.kernels_asymmetric.kernel_pdf_invgauss
    • statsmodels.nonparametric.kernels_asymmetric.kernel_pdf_lognorm
    • statsmodels.nonparametric.kernels_asymmetric.kernel_pdf_recipinvgauss
    • statsmodels.nonparametric.kernels_asymmetric.kernel_pdf_weibull
    • statsmodels.nonparametric.kernels_asymmetric.kernel_cdf_beta
    • statsmodels.nonparametric.kernels_asymmetric.kernel_cdf_beta2
    • statsmodels.nonparametric.kernels_asymmetric.kernel_cdf_bs
    • statsmodels.nonparametric.kernels_asymmetric.kernel_cdf_gamma
    • statsmodels.nonparametric.kernels_asymmetric.kernel_cdf_gamma2
    • statsmodels.nonparametric.kernels_asymmetric.kernel_cdf_invgamma
    • statsmodels.nonparametric.kernels_asymmetric.kernel_cdf_invgauss
    • statsmodels.nonparametric.kernels_asymmetric.kernel_cdf_lognorm
    • statsmodels.nonparametric.kernels_asymmetric.kernel_cdf_recipinvgauss
    • statsmodels.nonparametric.kernels_asymmetric.kernel_cdf_weibull
  • Generalized Method of Moments gmm
  • Other Models miscmodels
  • Multivariate Statistics multivariate
  • Statistics stats
  • Contingency tables
  • Multiple Imputation with Chained Equations
  • Treatment Effects treatment
  • Empirical Likelihood emplike
  • Distributions
  • Graphics
  • Input-Output iolib
  • Tools
  • Working with Large Data Sets
  • Optimization
  • The Datasets Package
  • Sandbox
  • User Guide
  • Nonparametric Methods nonparametric
  • statsmodels.nonparametric.kernel_regression.KernelReg
  • statsmodels.nonparametric.kernel_regression.KernelReg.loo_likelihood

statsmodels.nonparametric.kernel_regression.KernelReg.loo_likelihood#

KernelReg.loo_likelihood()#

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