Testing independence and goodness-of-fit in linear models
نویسندگان
چکیده
منابع مشابه
On Testing Independence and Goodness-of-fit in Linear Models
We consider a linear regression model and propose an omnibus test to simultaneously check the assumption of independence between the error and the predictor variables, and the goodness-of-fit of the parametric model. Our approach is based on testing for independence between the residual and the predictor using the recently developed Hilbert-Schmidt independence criterion, see [GFT+08]. The prop...
متن کاملDifferentially Private Chi-Squared Hypothesis Testing: Goodness of Fit and Independence Testing
Hypothesis testing is a useful statistical tool in determining whether a given model should be rejected based on a sample from the population. Sample data may contain sensitive information about individuals, such as medical information. Thus it is important to design statistical tests that guarantee the privacy of subjects in the data. In this work, we study hypothesis testing subject to differ...
متن کاملGoodness-of-fit tests in semi-linear models
Specification tests for the error distribution are proposed in semi–linear models, including the partial linear model and additive models. The tests utilize an integrated distance involving the empirical characteristic function of properly estimated residuals. These residuals are obtained from an initial estimation step involving a combination of penalized least squares and smoothing techniques...
متن کاملTesting Goodness of Fit of Random Graph Models
Random graphs are matrices with independent 0–1 elements with probabilities determined by a small number of parameters. One of the oldest models is the Rasch model where the odds are ratios of positive numbers scaling the rows and columns. Later Persi Diaconis with his coworkers rediscovered the model for symmetric matrices and called the model beta. Here we give goodness-of-fit tests for the m...
متن کاملGoodness-of-fit testing for accident models with low means.
The modeling of relationships between motor vehicle crashes and underlying factors has been investigated for more than three decades. Recently, many highway safety studies have documented the use of negative binomial (NB) regression models. On rare occasions, the Poisson model may be the only alternative especially when crash sample mean is low. Pearson's X(2) and the scaled deviance (G(2)) are...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Biometrika
سال: 2014
ISSN: 0006-3444,1464-3510
DOI: 10.1093/biomet/asu026