Multi-Locus Penetrance Variance Analysis Method for Association Study in Complex Diseases

2005 ◽  
Vol 60 (3) ◽  
pp. 143-149 ◽  
Author(s):  
Xiangqing Sun ◽  
Zhongqi Zhang ◽  
Yulong Zhang ◽  
Xuegong Zhang ◽  
Yanda Li
Keyword(s):  
Association Study ◽  
Complex Diseases ◽  
Variance Analysis ◽  
Analysis Method

Association study designs for complex diseases

2001 ◽  
Vol 2 (2) ◽  
pp. 91-99 ◽  
Author(s):  
Lon R. Cardon ◽  
John I. Bell
Keyword(s):  
Association Study ◽  
Complex Diseases ◽  
Study Designs

Research of Shell PTDF Shrink Model

2014 ◽  
Vol 494-495 ◽  
pp. 332-336 ◽  
Author(s):  
Hong Jun Li ◽  
Dong Feng Wang ◽  
Long Yan ◽  
Xing Tang ◽  
Zhi Quan Xiao
Keyword(s):  
Regression Analysis ◽  
Analysis Data ◽  
Variance Analysis ◽  
Analysis Method ◽  
Pressure Time ◽  
Two Factors ◽  
Main Factors ◽  
Set Up ◽  
The Relationship ◽  
Tube Shell

Stress (P) and pressure time (T) are the two main factors which affect the bayonet tube shell shrinking size. In this paper, we study this two factors. Double factors regression analysis and variance analysis method were used to analysis data. PT tube shell shrinkage model is set up to explore the correlation of tube shell shrinkage size and pressure (P) and the pressure time (T) and its change rule. Results show that the established PT contraction model can well reflect the relationship between the tube shell shrinkage size and the PT factors.

scholarly journals Dynamic Allan Variance Analysis Method with Time-Variant Window Length Based on Fuzzy Control

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Shanshan Gu ◽  
Jianye Liu ◽  
Qinghua Zeng ◽  
Shaojun Feng ◽  
Pin Lv
Keyword(s):  
Fuzzy Control ◽  
Fuzzy Controller ◽  
Allan Variance ◽  
Variance Analysis ◽  
Identification Accuracy ◽  
Evaluation Index ◽  
Window Length ◽  
Analysis Method ◽  
Accuracy Requirement ◽  
Performance Evaluation Index

To solve the problem that dynamic Allan variance (DAVAR) with fixed length of window cannot meet the identification accuracy requirement of fiber optic gyro (FOG) signal over all time domains, a dynamic Allan variance analysis method with time-variant window length based on fuzzy control is proposed. According to the characteristic of FOG signal, a fuzzy controller with the inputs of the first and second derivatives of FOG signal is designed to estimate the window length of the DAVAR. Then the Allan variances of the signals during the time-variant window are simulated to obtain the DAVAR of the FOG signal to describe the dynamic characteristic of the time-varying FOG signal. Additionally, a performance evaluation index of the algorithm based on radar chart is proposed. Experiment results show that, compared with different fixed window lengths DAVAR methods, the change of FOG signal with time can be identified effectively and the evaluation index of performance can be enhanced by 30% at least by the DAVAR method with time-variant window length based on fuzzy control.

Sign in / Sign up

Export Citation Format

Share Document