A Nonparametric Bootstrap Test and Estimation for Change
نویسندگان
چکیده
منابع مشابه
Statistical Topology Using the Nonparametric Density Estimation and Bootstrap Algorithm
This paper presents approximate confidence intervals for each function of parameters in a Banach space based on a bootstrap algorithm. We apply kernel density approach to estimate the persistence landscape. In addition, we evaluate the quality distribution function estimator of random variables using integrated mean square error (IMSE). The results of simulation studies show a significant impro...
متن کاملA Consistent Nonparametric Bootstrap Test of Exogeneity
We propose a way of testing exogeneity of an explanatory variable without any parametric assumptions in the presence of a conditional "instrumental variable". A testable implication is derived that if an explanatory variable is exogenous, the conditional distribution of the outcome given explanatory variables is independent of the instrumental variable. We propose a consistent nonparametric boo...
متن کاملA MODIFICATION ON RIDGE ESTIMATION FOR FUZZY NONPARAMETRIC REGRESSION
This paper deals with ridge estimation of fuzzy nonparametric regression models using triangular fuzzy numbers. This estimation method is obtained by implementing ridge regression learning algorithm in the La- grangian dual space. The distance measure for fuzzy numbers that suggested by Diamond is used and the local linear smoothing technique with the cross- validation procedure for selecting t...
متن کاملA Nonparametric Hypothesis Test via the Bootstrap Resampling
This paper adapts an already existing nonparametric hypothesis test to the bootstrap framework. The test utilizes the nonparametric kernel regression method to estimate a measure of distance between the models stated under the null hypothesis. The bootstraped version of the test allows to approximate errors involved in the asymptotic hypothesis test.
متن کاملBootstrap Methods for the Nonparametric
A completely nonparametric approach to population bioequivalence in crossover trials has been suggested by Munk and Czado (1999). It is based on the Mallows (1972) metric as a nonparametric distance measure which allows the comparison between the entire distribution functions of test and reference formulations. It was shown that a separation between carry-over and period eeects is not possible ...
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: Communications for Statistical Applications and Methods
سال: 2007
ISSN: 2287-7843
DOI: 10.5351/ckss.2007.14.2.443