PPT-Non-iterative Joint and Individual Variation Explained

Qing Feng Joint Work with JS Marron Jan Hannig Date 20140925 1 Era Challenge 2 Data Challenges MultiBlock data X Y     S ubjects Feature Set 1 Feature Set 2 R apid growth of sources to obtain data. Bashh. & . Bhiva. National Audit of Partner Notification of Adults Newly Diagnosed with HIV infection. __________________________________. Michael . Rayment . on Behalf of the . Bashh. National Audit Group and . and Economic . Development: . Evidence from Rainfall Data . Lewis Davis. Department of Economics. Union College. University of Perugia. May 15, 2014 . Is a taste for individual responsibility good for economic development?. Computations. K-means. Performance of K-Means. Smith Waterman is a non iterative case and of course runs fine. Matrix Multiplication . 64 cores. Square blocks Twister. Row/Col . decomp. Twister. (JKO) . Stakeholders Meeting. Worldwide Joint Training and Scheduling Conference. Colorado Springs, CO. 19 September 2012. UNCLASSIFIED. Purpose. . Gain JKO . Stakeholders’ . consensus on . FY13 JKO . Goal: Use inverse variation and joint variation models.. Warm-up. Simplify:. Inverse Variation. 2 variables, x and y, vary inversely if:. k is called the constant of variation.. Example 1. Tell whether x and y show direct variation, inverse variation, or neither:. The Coefficient Of Determination. What is r. 2. ?. The coefficient of determination . (. r-sq, r. 2. ). Mathematically it . is . the r-value squared . (r. 2. = r . * r. ). The LSRL (least-squares regression line or y-hat) is just . JIVE for Data Integration. Qing Feng. Joint Work with Jan . Hannig. , J.S. Marron. Mar. . 24. th. , 2016. 1. Figure : The Cancer Genome Atlas Research Network, Weinstein, J.N., . Collisson. , E.A., Mills, G.B., Shaw, K.M., . The Coefficient Of Determination. What is r. 2. ?. The coefficient of determination . (. r-sq, r. 2. ). Mathematically it . is . the r-value squared . (r. 2. = r . * r. ). The LSRL (least-squares regression line or y-hat) is just . Inverse variation. Recall: variables . x . and . y. show direct variation if . for some nonzero constant . a. .. *Note: the general equation . for inverse variation can be rewritten as . ..  . Classifying direct/inverse variation. Computations. K-means. Performance of K-Means. Smith Waterman is a non iterative case and of course runs fine. Matrix Multiplication . 64 cores. Square blocks Twister. Row/Col . decomp. Twister. Direct Variation. y varies directly as x if there is a nonzero constant, k, such that . y = . kx. *k is called the constant of variation. Plug in the two values you have and solve for the missing variable. Liz Cirulli. Assistant Research Professor. Duke Center for Applied Genomics and Precision Medicine (CAGPM). 4/27/15. Advantages to studying healthy variation. Most “healthy” traits not studied genetically at all. Associate Professor. Variation. . Importance of variation. . Types of variation. . Phenotypic variation. Partitioning of phenotypic variation. Causes of phenotypic variation. G. enetic variation. Notes: We conducted this analysis by regressing median premiums from the Medical Expenditure Panel . Survey-Insurance . Component (MEPS-IC) on state measures of health care costs, plan characteristics, workforce composition, and demographics from a...