scholarly journals Statistical inference for the shape parameter change-point estimator in negative associated gamma distribution

2013 ◽  
Vol 2013 (1) ◽  
Author(s):  
Chang-chun Tan ◽  
Bai-qi Miao ◽  
Xing-cai Zhou
Keyword(s):  
Statistical Inference ◽  
Gamma Distribution ◽  
Change Point ◽  
Shape Parameter ◽  
Parameter Change ◽  
Point Estimator

scholarly journals Change Point Estimation in Panel Data without Boundary Issue

2016 ◽  
Author(s):  
Barbora Peštová ◽  
Michal Pešta
Keyword(s):  
Panel Data ◽  
Change Point ◽  
Structural Breaks ◽  
Break Point ◽  
Point Estimation ◽  
The Novel ◽  
Structure Estimation ◽  
Change Point Estimation ◽  
Point Estimator ◽  
First Time

Panel data of our interest consist of a moderate number of panels, while the panels contain a small number of observations. An estimator of common breaks in panel means without a boundary issue for this kind of scenario is proposed. In particular, the novel estimator is able to detect a common break point even when the change happens immediately after the first time point or just before the last observation period. Another advantage of the elaborated change point estimator is that it results in the last observation in situations with no structural breaks. The consistency of the change point estimator in panel data is established. The results are illustrated through a simulation study. As a by-product of the developed estimation technique, a theoretical utilization for correlation structure estimation, hypothesis testing, and bootstrapping in panel data is demonstrated. A practical application to non-life insurance is presented as well.

Efficient Change-Points Detection For Genomic Sequences Via Cumulative Segmented Regression

2021 ◽  
Author(s):  
Shengji Jia ◽  
Lei Shi
Keyword(s):  
Change Point ◽  
Serial Correlation ◽  
Copy Number Variations ◽  
Change Points ◽  
Supplementary Information ◽  
Genomic Sequences ◽  
Segmented Regression ◽  
Computationally Efficient ◽  
R Program ◽  
Point Estimator

Abstract Motivation Knowing the number and the exact locations of multiple change points in genomic sequences serves several biological needs. The cumulative segmented algorithm (cumSeg) has been recently proposed as a computationally efficient approach for multiple change-points detection, which is based on a simple transformation of data and provides results quite robust to model mis-specifications. However, the errors are also accumulated in the transformed model so that heteroscedasticity and serial correlation will show up, and thus the variations of the estimated change points will be quite different, while the locations of the change points should be of the same importance in the original genomic sequences. Results In this study, we develop two new change-points detection procedures in the framework of cumulative segmented regression. Simulations reveal that the proposed methods not only improve the efficiency of each change point estimator substantially but also provide the estimators with similar variations for all the change points. By applying these proposed algorithms to Coriel and SNP genotyping data, we illustrate their performance on detecting copy number variations. Supplementary information The proposed algorithms are implemented in R program and are available at Bioinformatics online.

On the quantiles of the gamma and F distributions

1978 ◽  
Vol 15 (2) ◽  
pp. 426-432 ◽  
Author(s):  
I. W. Saunders ◽  
P. A. P. Moran
Keyword(s):  
Gamma Distribution ◽  
Shape Parameter

We show, in the context of a neurobiological problem, that ζ a(α)−ζ a(β) increases with a, while ζ a (α)/ζ a (β) decreases with a, where 0 < β < α < 1 and ζ a (α) is the α th quantile of either the gamma distribution with shape parameter a, or a scaled F distribution with parameters 2a and 2m for any m.

Detection of Uterine MMG Contractions Using a Multiple Change Point Estimator and the K-Means Cluster Algorithm

2008 ◽  
Vol 55 (2) ◽  
pp. 453-467 ◽  
Author(s):  
Patricio S. La Rosa ◽  
Arye Nehorai ◽  
Hari Eswaran ◽  
Curtis L. Lowery ◽  
Hubert Preissl
Keyword(s):  
Change Point ◽  
Cluster Algorithm ◽  
Point Estimator

scholarly journals Distribution of Myosin Attachment Times Predicted from Viscoelastic Mechanics of Striated Muscle

2011 ◽  
Vol 2011 ◽  
pp. 1-16 ◽  
Author(s):  
Bradley M. Palmer ◽  
Yuan Wang ◽  
Mark S. Miller
Keyword(s):  
Exponential Distribution ◽  
Gamma Distribution ◽  
Shape Parameter ◽  
Striated Muscle ◽  
Scale Parameter ◽  
Viscoelastic Model ◽  
A Value ◽  
Temporal Events ◽  
Single Exponential

We demonstrate that viscoelastic mechanics of striated muscle, measured as elastic and viscous moduli, emerge directly from the myosin crossbridge attachment time,tatt, also called time-on. The distribution oftattwas modeled using a gamma distribution with shape parameter,p, and scale parameter,β. At 5 mM MgATP,βwas similar between mouseα-MyHC (16.0±3.7 ms) andβ-MyHC (17.9±2.0 ms), andpwas higher (P<0.05) forβ-MyHC (5.6±0.4no units) compared toα-MyHC (3.2±0.9). At 1 mM MgATP,papproached a value of 10 in both isoforms, butβrose only in theβ-MyHC (34.8±5.8 ms). The estimated meantatt(i.e.,pβproduct) was longer in theβ-MyHC compared toα-MyHC, and became prolonged in both isoforms as MgATP was reduced as expected. The application of our viscoelastic model to these isoforms and varying MgATP conditions suggest thattattis better modeled as a gamma distribution due to its representing multiple temporal events occurring withintattcompared to a single exponential distribution which assumes only one temporal event withintatt.

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