Simultaneous Regression and Selection in Nonlinear Modal Model Identification
نویسندگان
چکیده
منابع مشابه
Regularized simultaneous model selection in multiple quantiles regression
Simultaneously estimating multiple conditional quantiles is often regarded as a more appropriate regression tool than the usual conditional mean regression for exploring the stochastic relationship between the response and covariates. When multiple quantile regressions are considered, it is of great importance to share strength among them. In this paper, we propose a novel regularization method...
متن کاملA New Regression Model: Modal Linear Regression
The mode of a distribution provides an important summary of data and is often estimated based on some non-parametric kernel density estimator. This article develops a new data analysis tool called modal linear regression in order to explore highdimensional data. Modal linear regression models the conditional mode of a response Y given a set of predictors x as a linear function of x. Modal linea...
متن کاملA diagnostic method for simultaneous feature selection and outlier identification in linear regression
A diagnostic method along the lines of forward search is proposed to simultaneously study the effect of individual observations and features on the inferences made in linear regression. The method operates by appending dummy variables to the data matrix and performing backward selection on the augmented matrix. It outputs sequences of feature–outlier combinations which can be evaluated by plots...
متن کاملA method for simultaneous variable selection and outlier identification in linear regression*
We suggest a method for simultaneous variable selection and outlier identification based on the computation of posterior model probabilities. This avoids the problem that the model you select depends upon the order in which variable selection and outlier identification are carried out. Our method can find multiple outliers and appears to be successful in identifying masked outliers. We also add...
متن کاملRobust nonlinear model identification methods using forward regression
In this correspondence new robust nonlinear model construction algorithms for a large class of linear-in-the-parameters models are introduced to enhance model robustness via combined parameter regularization and new robust structural selective criteria. In parallel to parameter regularization, we use two classes of robust model selection criteria based on either experimental design criteria tha...
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: Vibration
سال: 2021
ISSN: 2571-631X
DOI: 10.3390/vibration4010016