Physical Sciences and Mathematics Commons^™

On Covariance Structure In Noisy, Big Data, Randy Paffenroth, Ryan Nong, Philip Du Toit

Randy C. Paffenroth

Herein we describe theory and algorithms for detecting covariance structures in large, noisy data sets. Our work uses ideas from matrix completion and robust principal component analysis to detect the presence of low-rank covariance matrices, even when the data is noisy, distorted by large corruptions, and only partially observed. In fact, the ability to handle partial observations combined with ideas from randomized algorithms for matrix decomposition enables us to produce asymptotically fast algorithms. Herein we will provide numerical demonstrations of the methods and their convergence properties. While such methods have applicability to many problems, including mathematical finance, crime analysis, and …

Hamamatsu Flash4.0 Scmos Exposure Time Series, George Mcnamara

George McNamara

Hamamatsu FLASH4.0 scientific cMOS camera exposure time series are pairs of images of:

1 millisecond (00,001ms series)

10 millisecond (00,010ms series)

100 millisecond (00,100ms series)

1,000 millisecond (01,000ms series)

4,000 millisecond (04,000ms series)

10,000 millisecond (10,000ms series)

I also included:

* difference images (exposure 2 minus exposure 1 plus 100 intensity values).

* a series of eleven 1 second (1,000 ms) exposure time images in a multi-plane TIFF file (different images than the pair of 1,000ms images above).

* Stack Arithmetic: Median, Average, Minimum, Maximum, of the eleven plane series (Stack Arithmetic is a MetaMorph command).

These images were acquired …

Gee-2 R Data Files, Joseph Hilbe

Joseph M Hilbe

Generalized Estimating Equations, 2nd edition Publsihed: 10 December, 2012 R Data Files

Gee-2 R Scripts And Functions, Joseph Hilbe

Joseph M Hilbe

Generalized Estimating Equations, 2nd edition Published: 10 December, 2012 R scripts and functions

Census 2000 Demographic And Housing Profile Reports, Mark Salling, Ellen Cyran, Sharon Bliss

Ellen Cyran

No abstract provided.

Sas Macro: Kappa Statistic For Clustered Matched-Pair Data, Zhao Yang

Zhao (Tony) Yang, Ph.D.

The SAS macro was developed to calculate the kappa statistic for the clustered matched-pair data.