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Search Results: 1 - 10 of 19013 matches for " Generalized likelihood ratio test "
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Generalized Likelihood Ratio Tests for Varying-Coefficient Models with Censored Data  [PDF]
Rong Jiang, Wei-Min Qian
Open Journal of Statistics (OJS) , 2011, DOI: 10.4236/ojs.2011.11003
Abstract: In this paper, we extend the generalized likelihood ratio test to the varying-coefficient models with censored data. We investigate the asymptotic behavior of the proposed test and demonstrate that its limiting null distribution follows a distribution, with the scale constant and the number of degree of freedom being independent of nuisance parameters or functions, which is called the wilks phenomenon. Both simulated and real data examples are given to illustrate the performance of the testing approach.
Fuzzy Varying Coefficient Bilinear Regression of Yield Series  [PDF]
Ting He, Qiujun Lu
Journal of Data Analysis and Information Processing (JDAIP) , 2015, DOI: 10.4236/jdaip.2015.33006
Abstract: We construct a fuzzy varying coefficient bilinear regression model to deal with the interval financial data and then adopt the least-squares method based on symmetric fuzzy number space. Firstly, we propose a varying coefficient model on the basis of the fuzzy bilinear regression model. Secondly, we develop the least-squares method according to the complete distance between fuzzy numbers to estimate the coefficients and test the adaptability of the proposed model by means of generalized likelihood ratio test with SSE composite index. Finally, mean square errors and mean absolutely errors are employed to evaluate and compare the fitting of fuzzy auto regression, fuzzy bilinear regression and fuzzy varying coefficient bilinear regression models, and also the forecasting of three models. Empirical analysis turns out that the proposed model has good fitting and forecasting accuracy with regard to other regression models for the capital market.
David D. Hanagal
Journal of Reliability and Statistical Studies , 2009,
Abstract: Block (1975) extended bivariate exponential distributions (BVEDs) of Freund (1961)and Proschan and Sullo (1974) to multivariate case and called them as Generalized Freund-Weinman's multivariate exponential distributions (MVEDs). In this paper, we obtain MLEs of theparameters and large sample test for testing independence and symmetry of k components in thegeneralized Freund-Weinman's MVEDs.
A Novel Decoder for Unknown Diversity Channels Employing Space-Time Codes
Erez Elona,Feder Meir
EURASIP Journal on Advances in Signal Processing , 2002,
Abstract: We suggest new decoding techniques for diversity channels employing space time codes (STC) when the channel coefficients are unknown to both transmitter and receiver. Most of the existing decoders for unknown diversity channels employ training sequence in order to estimate the channel. These decoders use the estimates of the channel coefficients in order to perform maximum likelihood (ML) decoding. We suggest an efficient implementation of the generalized likelihood ratio test (GLRT) algorithm that improves the performance with only slight increase in complexity. We also suggest an energy weighted decoder (EWD) that shows additional improvement without further increase in the computational complexity.
A Particle Filtering Approach to Change Detection for Nonlinear Systems
P. S. Krishnaprasad,Babak Azimi-Sadjadi
EURASIP Journal on Advances in Signal Processing , 2004, DOI: 10.1155/s1687617204408051
Abstract: We present a change detection method for nonlinear stochastic systems based on particle filtering. We assume that the parameters of the system before and after change are known. The statistic for this method is chosen in such a way that it can be calculated recursively while the computational complexity of the method remains constant with respect to time. We present simulation results that show the advantages of this method compared to linearization techniques.
Computationally Efficient Blind Code Synchronization for Asynchronous DS-CDMA Systems with Adaptive Antenna Arrays
Chia-Chang Hu
EURASIP Journal on Advances in Signal Processing , 2005, DOI: 10.1155/asp.2005.683
Abstract: A novel space-time adaptive near-far robust code-synchronization array detector for asynchronous DS-CDMA systems is developed in this paper. There are the same basic requirements that are needed by the conventional matched filter of an asynchronous DS-CDMA system. For the real-time applicability, a computationally efficient architecture of the proposed detector is developed that is based on the concept of the multistage Wiener filter (MWF) of Goldstein and Reed. This multistage technique results in a self-synchronizing detection criterion that requires no inversion or eigendecomposition of a covariance matrix. As a consequence, this detector achieves a complexity that is only a linear function of the size of antenna array (J), the rank of the MWF (M), the system processing gain (N), and the number of samples in a chip interval (S), that is, ° ’ a(JMNS). The complexity of the equivalent detector based on the minimum mean-squared error (MMSE) or the subspace-based eigenstructure analysis is a function of ° ’ a((JNS)3). Moreover, this multistage scheme provides a rapid adaptive convergence under limited observation-data support. Simulations are conducted to evaluate the performance and convergence behavior of the proposed detector with the size of the J-element antenna array, the amount of the L-sample support, and the rank of the M-stage MWF. The performance advantage of the proposed detector over other DS-CDMA detectors is investigated as well.
Comparison of Statistical Data Models for Identifying Differentially Expressed Genes Using a Generalized Likelihood Ratio Test
Kok-Yong Seng,Robb W. Glenny,David K. Madtes,Mary E. Spilker
Gene Regulation and Systems Biology , 2008,
Abstract: Currently, statistical techniques for analysis of microarray-generated data sets have deficiencies due to limited understanding of errors inherent in the data. A generalized likelihood ratio (GLR) test based on an error model has been recently proposed to identify differentially expressed genes from microarray experiments. However, the use of different error structures under the GLR test has not been evaluated, nor has this method been compared to commonly used statistical tests such as the parametric t-test. The concomitant effects of varying data signal-to-noise ratio and replication number on the performance of statistical tests also remain largely unexplored. In this study, we compared the effects of different underlying statistical error structures on the GLR test’s power in identifying differentially expressed genes in microarray data. We evaluated such variants of the GLR test as well as the one sample t-test based on simulated data by means of receiver operating characteristic (ROC) curves. Further, we used bootstrapping of ROC curves to assess statistical significance of differences between the areas under the curves. Our results showed that i) the GLR tests outperformed the t-test for detecting differential gene expression, ii) the identity of the underlying error structure was important in determining the GLR tests’ performance, and iii) signal-to-noise ratio was a more important contributor than sample replication in identifying statistically significant differential gene expression.
Application of Project Pursuit in Hyperspectral Anomaly Detection

Li Zhi-yong,Kuang Gang-yao,Zou Huan-xin,

电子与信息学报 , 2004,
Abstract: In this paper, a new method of hyperspectral anomaly detection based on project pursuit is presented. The Generalized Likelihood Ratio Test(GLRT) is used to establish a binary hypotheses detector and estimates the unknown parameters that represent the background in the detector from the image. Target information, the key parameter, is got by using project pursuit approach to search anomaly information. The algorithm reduces the dependence of pre-information, enhances the arithmetic practicability. At the same time, project pursuit approach can extract target information efficiently and improve the effect of anomaly detection.
Performance of Cooperative Eigenvalue Spectrum Sensing with a Realistic Receiver Model under Impulsive Noise
Dayan A. Guimar?es,Rausley A. A. de Souza,André N. Barreto
Journal of Sensor and Actuator Networks , 2013, DOI: 10.3390/jsan2010046
Abstract: In this paper we present a unified comparison of the performance of four detection techniques for centralized data-fusion cooperative spectrum sensing in cognitive radio networks under impulsive noise, namely, the eigenvalue-based generalized likelihood ratio test (GLRT), the maximum-minimum eigenvalue detection (MMED), the maximum eigenvalue detection (MED), and the energy detection (ED). We consider two system models: an implementation-oriented model that includes the most relevant signal processing tasks realized by a real cognitive radio receiver, and the theoretical model conventionally adopted in the literature. We show that under the implementation-oriented model, GLRT and MMED are quite robust under impulsive noise, whereas the performance of MED and ED is drastically degraded. We also show that performance under the conventional model can be too pessimistic if impulsive noise is present, whereas it can be too optimistic in the absence of this impairment. We also discuss the fact that impulsive noise is not such a severe problem when we take into account the more realistic implementation-oriented model.
Variabilidade amostral das séries mensais de precipita??o pluvial em duas regi?es do Brasil: Pelotas-RS e Campinas-SP
Blain, Gabriel Constantino;Kayano, Mary Toshie;Camargo, Marcelo Bento Paes de;Lulu, Jorge;
Revista Brasileira de Meteorologia , 2009, DOI: 10.1590/S0102-77862009000100001
Abstract: the present work evaluated the sample variability of the gamma distribution parameters fitted to monthly precipitation series in the regions of campinas-sp and pelotas-rs, which have data for the 1890-2006 and 1890-2005 periods, respectively. so, the sample spaces considered were of 58, 39 and 29 years for campinas, and of 58 and 29 years for pelotas. analyses were done using the likelihood ratio test. the analyses showed significant sample alterations. no trend was detected in monthly precipitation series of the region of campinas-sp. increasing trends was detected in the monthly precipitation series of the region of pelotas-rs considering the 1948 to 1976 and 1977 to 2005 samples.
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