A goodness-of-fit test for stochastic block models
نویسندگان
چکیده
منابع مشابه
Goodness-of-fit test for stochastic volatility models
In this paper, we propose a goodness of fit test for continuous time stochastic volatility models based on discretely sampled observations. The proposed test is constructed by measuring deviations between the empirical and true characteristic functions obtained from the hypothesized stochastic volatility model. In this study, both the test statistics based on the fixed and decreasing sampling s...
متن کاملA Goodness of Fit Test For Exponentiality Based on Lin-Wong Information
In this paper, we introduce a goodness of fit test for expo- nentiality based on Lin-Wong divergence measure. In order to estimate the divergence, we use a method similar to Vasicek’s method for estimat- ing the Shannon entropy. The critical values and the powers of the test are computed by Monte Carlo simulation. It is shown that the proposed test are competitive with other tests of exponentia...
متن کاملA goodness-of-fit test for structural nested mean models
Coarse structural nested mean models are tools to estimate treatment effects from longitudinal observational data with time-dependent confounding. There is, however, no guidance on how to specify the treatment effect model, and model misspecification can lead to bias. We derive a goodness-of-fit test based on modified overidentification restrictions tests for evaluating a treatment effect model...
متن کاملA New Goodness-of-Fit Test for a Distribution by the Empirical Characteristic Function
Extended Abstract. Suppose n i.i.d. observations, X1, …, Xn, are available from the unknown distribution F(.), goodness-of-fit tests refer to tests such as H0 : F(x) = F0(x) against H1 : F(x) $neq$ F0(x). Some nonparametric tests such as the Kolmogorov--Smirnov test, the Cramer-Von Mises test, the Anderson-Darling test and the Watson test have been suggested by comparing empirical ...
متن کاملNonparametric Goodness-of-fit Test for Heteroscedastic Regression Models
For the heteroscedastic nonparametric regression model Yni = m(xni)+σ(xni)2ni, i = 1, ..., n, a novel method is proposed for testing that the regression function m is constant. The test statistic is motivated by recent developments in the asymptotic theory for analysis of variance when the number of factor levels is large. Its asymptotic normality is derived under the null hypothesis and suitab...
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: The Annals of Statistics
سال: 2016
ISSN: 0090-5364
DOI: 10.1214/15-aos1370