scholarly journals Least square and Empirical Bayes Approaches for Estimating Random Change Points

2021 ◽  
Vol 7 (1) ◽  
pp. 1-12
Author(s):  
Yuanjia Wang ◽  
Yixin Fang
Keyword(s):  
Empirical Bayes ◽  
Least Square ◽  
Change Points ◽  
Random Change

Generalized monotonic regression using random change points

2003 ◽  
Vol 22 (4) ◽  
pp. 623-638 ◽  
Author(s):  
C. C. Holmes ◽  
N. A. Heard
Keyword(s):  
Change Points ◽  
Monotonic Regression ◽  
Random Change

scholarly journals PROC QTL—A SAS Procedure for Mapping Quantitative Trait Loci

2009 ◽  
Vol 2009 ◽  
pp. 1-3 ◽  
Author(s):  
Zhiqiu Hu ◽  
Shizhong Xu
Keyword(s):  
Statistical Analysis ◽  
Quantitative Trait Loci ◽  
Qtl Mapping ◽  
Quantitative Trait ◽  
Empirical Bayes ◽  
Least Square ◽  
Statistical Analysis System ◽  
Trait Loci ◽  
Analysis System ◽  
Almost All

Statistical analysis system (SAS) is the most comprehensive statistical analysis software package in the world. It offers data analysis for almost all experiments under various statistical models. Each analysis is performed using a particular subroutine, called a procedure (PROC). For example, PROC ANOVA performs analysis of variances. PROC QTL is a user-defined SAS procedure for mapping quantitative trait loci (QTL). It allows users to perform QTL mapping for continuous and discrete traits within the SAS platform. Users of PROC QTL are able to take advantage of all existing features offered by the general SAS software, for example, data management and graphical treatment. The current version of PROC QTL can perform QTL mapping for all line crossing experiments using maximum likelihood (ML), least square (LS), iteratively reweighted least square (IRLS), Fisher scoring (FISHER), Bayesian (BAYES), and empirical Bayes (EBAYES) methods.

scholarly journals A MOSUM procedure for the estimation of multiple random change points

Bernoulli ◽  
2018 ◽  
Vol 24 (1) ◽  
pp. 526-564 ◽  
Author(s):  
Birte Eichinger ◽  
Claudia Kirch
Keyword(s):  
Change Points ◽  
Random Change

Least-square refinement of structure parameters from CBED integrated intensities: application to determination of temperature factors in Y BA2CU3O7

1992 ◽  
Vol 50 (2) ◽  
pp. 1456-1457
Author(s):  
Kjersti Gjønnes ◽  
Jon Gjønnes
Keyword(s):  
Least Square ◽  
Measured Intensity ◽  
Structure Information ◽  
Accurate Temperature ◽  
Least Square Fit ◽  
Case Application ◽  
Integrated Intensities ◽  
Temperature Factors ◽  
Narrow Bands

Electron diffraction intensities can be obtained at large scattering angles (sinθ/λ ≥ 2.0), and thus structure information can be collected in regions of reciprocal space that are not accessable with other diffraction methods. LACBED intensities in this range can be utilized for determination of accurate temperature factors or for refinement of coordinates. Such high index reflections can usually be treated kinematically or as a pertubed two-beam case. Application to Y Ba2Cu3O7 shows that a least square refinememt based on integrated intensities can determine temperature factors or coordinates.LACBED patterns taken in the (00l) systematic row show an easily recognisable pattern of narrow bands from reflections in the range 15 < l < 40 (figure 1). Integrated intensities obtained from measured intensity profiles after subtraction of inelastic background (figure 2) were used in the least square fit for determination of temperature factors and refinement of z-coordinates for the Ba- and Cu-atoms.

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