Multivariate INAR(1) regression modelsMultivariate mixed Poisson-Generalized Inverse GaussianCorrelated time seriesMaximum likelihood estimationIn this paper, we present a novel family of multivariate mixed Poisson-Generalized Inverse Gaussian INAR(1), MMPGIG-INAR(1), regression models for modelling time...
We define a new four-parameter model called the odd log-logistic generalized inverse Gaussian distribution which extends the generalized inverse Gaussian and inverse Gaussian distributions. We obtain some structural properties of the new distribution. We construct an extended regression model based on this...
mdl = stepwiseglm(tbl) creates a generalized linear regression model for the variables in the table tbl using stepwise regression to add or remove predictors, starting from a constant model. stepwiseglm uses the last variable of tbl as the response variable. stepwiseglm uses forward and backward...
mdl= fitglm(___,modelspec)returns a generalized linear regression model of the type you specify inmodelspec. example mdl= fitglm(___,Name,Value)returns a generalized linear regression model with additional options specified by one or moreName,Valuepair arguments. ...
'inverse gaussian'-2f(μ) = 1/μ2μ= (Xb)–1/2 Tips The generalized linear modelmdlis a standard linear model unless you specify otherwise with theDistributionname-value pair. For methods such asplotResidualsordevianceTest, or properties of theGeneralizedLinearModelobject, seeGeneralizedLinearMode...
This MATLAB function returns a vector b of coefficient estimates for a generalized linear regression model of the responses in y on the predictors in X, using the distribution distr.
Link:between the random and covariates X=(X(1),X(2),⋯,X(p))⊤:μ(X)=X⊤βX=(X(1),X(2),⋯,X(p))⊤:μ(X)=X⊤β Ageneralized linear model (GLM)generalizes normal linear regression models in the following directions. ...
Inverse Gaussian Distribution (Wolfram MathWorld) » Regression (Wolfram MathWorld) » Permanent Citation Cite this as Darren Glosemeyer(2011), "Comparing Some Residuals for Generalized Linear Models" Wolfram Demonstrations Project. demonstrations.wolfram.com/ComparingSomeResidualsForGeneralizedLinearModels/...
本文简要介绍 pyspark.ml.regression.GeneralizedLinearRegression 的用法。 用法: class pyspark.ml.regression.GeneralizedLinearRegression(*, labelCol='label', featuresCol='features', predictionCol='prediction', family='gaussian', link=None, fitIntercept=True, maxIter=25, tol=1e-06, regParam=0.0, ...
A test statistic proposed by Li (1999) for testing the adequacy of heteroscedastic nonlinear regression models using nonparametric kernel smoothers is applied to testing for linearity in generalized linear models. Simulation results for models with centered gamma and inverse Gaussian errors are presented ...