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Articles 1 - 14 of 14
Full-Text Articles in Physical Sciences and Mathematics
Conference Proceedings 3rd International Scientific Conference On “Energy Systems With It” At Alvsjö Fair In Association With Energitinget March 16-17 2010, Dr. Erik Dahlquist, Dr. Jenny Palm
Conference Proceedings 3rd International Scientific Conference On “Energy Systems With It” At Alvsjö Fair In Association With Energitinget March 16-17 2010, Dr. Erik Dahlquist, Dr. Jenny Palm
Dr. Erik Dahlquist
2010 “The Energiting” is performed for the 12th time. The International Scientific conference is arranged for the 3rd time. The organisers are Swedish Energy Agency, Mälardalen University and the Research School for Energy Systems with LiU, KTH, UU and CTH. The first topic will be “Energy systems” covering use of renewable energy sources, energy conversion and process efficiency improvement with new technologies, as well as societal aspects of the introduction of new technologies. The second topic is “Energy and IT”. This covers energy and load management, interaction between production, distribution and “consumption”, usage of data for decision support and control, …
On Simulating Univariate And Multivariate Burr Type Iii And Type Xii Distributions, Todd C. Headrick, Mohan D. Pant, Yanyan Sheng
On Simulating Univariate And Multivariate Burr Type Iii And Type Xii Distributions, Todd C. Headrick, Mohan D. Pant, Yanyan Sheng
Mohan Dev Pant
This paper describes a method for simulating univariate and multivariate Burr Type III and Type XII distributions with specified correlation matrices. The methodology is based on the derivation of the parametric forms of a pdf and cdf for this family of distributions. The paper shows how shape parameters can be computed for specified values of skew and kurtosis. It is also demonstrated how to compute percentage points and other measures of central tendency such as the mode, median, and trimmed mean. Examples are provided to demonstrate how this Burr family can be used in the context of distribution fitting using …
Manifest Greatness The Final Original Version By Emmanuel Mario B Santos Aka Marc Guerrero, Emmanuel Mario B. Santos Aka Marc Guerrero
Manifest Greatness The Final Original Version By Emmanuel Mario B Santos Aka Marc Guerrero, Emmanuel Mario B. Santos Aka Marc Guerrero
Emmanuel Mario B Santos aka Marc Guerrero
MANIFEST GREATNESS vf24jan2010 WE COME TOGETHER THERE OUGHT TO BE NO POOR WE TAKE CHARGE.
Errata Negative Binomial Regression 1st Edition 1st Print, Joseph Hilbe
Errata Negative Binomial Regression 1st Edition 1st Print, Joseph Hilbe
Joseph M Hilbe
Errata for the first edition and printing of Negative Binomal Regression, August 2007. Many of the items listed here were corrected in the 2008 second printing.
International Diversification: A Copula Approach, Lorán Chollete, Victor De La Pena, Ching-Chih Lu
International Diversification: A Copula Approach, Lorán Chollete, Victor De La Pena, Ching-Chih Lu
Lorán Chollete
No abstract provided.
Wavelet-Based Functional Linear Mixed Models: An Application To Measurement Error–Corrected Distributed Lag Models, Elizabeth J. Malloy, Jeffrey S. Morris, Sara D. Adar, Helen Suh, Diane R. Gold, Brent A. Coull
Wavelet-Based Functional Linear Mixed Models: An Application To Measurement Error–Corrected Distributed Lag Models, Elizabeth J. Malloy, Jeffrey S. Morris, Sara D. Adar, Helen Suh, Diane R. Gold, Brent A. Coull
Jeffrey S. Morris
Frequently, exposure data are measured over time on a grid of discrete values that collectively define a functional observation. In many applications, researchers are interested in using these measurements as covariates to predict a scalar response in a regression setting, with interest focusing on the most biologically relevant time window of exposure. One example is in panel studies of the health effects of particulate matter (PM), where particle levels are measured over time. In such studies, there are many more values of the functional data than observations in the data set so that regularization of the corresponding functional regression coefficient …
Members’ Discoveries: Fatal Flaws In Cancer Research, Jeffrey S. Morris
Members’ Discoveries: Fatal Flaws In Cancer Research, Jeffrey S. Morris
Jeffrey S. Morris
A recent article published in The Annals of Applied Statistics (AOAS) by two MD Anderson researchers—Keith Baggerly and Kevin Coombes—dissects results from a highly-influential series of medical papers involving genomics-driven personalized cancer therapy, and outlines a series of simple yet fatal flaws that raises serious questions about the veracity of the original results. Having immediate and strong impact, this paper, along with related work, is providing the impetus for new standards of reproducibility in scientific research.
Statistical Contributions To Proteomic Research, Jeffrey S. Morris, Keith A. Baggerly, Howard B. Gutstein, Kevin R. Coombes
Statistical Contributions To Proteomic Research, Jeffrey S. Morris, Keith A. Baggerly, Howard B. Gutstein, Kevin R. Coombes
Jeffrey S. Morris
Proteomic profiling has the potential to impact the diagnosis, prognosis, and treatment of various diseases. A number of different proteomic technologies are available that allow us to look at many proteins at once, and all of them yield complex data that raise significant quantitative challenges. Inadequate attention to these quantitative issues can prevent these studies from achieving their desired goals, and can even lead to invalid results. In this chapter, we describe various ways the involvement of statisticians or other quantitative scientists in the study team can contribute to the success of proteomic research, and we outline some of the …
Informatics And Statistics For Analyzing 2-D Gel Electrophoresis Images, Andrew W. Dowsey, Jeffrey S. Morris, Howard G. Gutstein, Guang Z. Yang
Informatics And Statistics For Analyzing 2-D Gel Electrophoresis Images, Andrew W. Dowsey, Jeffrey S. Morris, Howard G. Gutstein, Guang Z. Yang
Jeffrey S. Morris
Whilst recent progress in ‘shotgun’ peptide separation by integrated liquid chromatography and mass spectrometry (LC/MS) has enabled its use as a sensitive analytical technique, proteome coverage and reproducibility is still limited and obtaining enough replicate runs for biomarker discovery is a challenge. For these reasons, recent research demonstrates the continuing need for protein separation by two-dimensional gel electrophoresis (2-DE). However, with traditional 2-DE informatics, the digitized images are reduced to symbolic data though spot detection and quantification before proteins are compared for differential expression by spot matching. Recently, a more robust and automated paradigm has emerged where gels are directly …
Bayesian Random Segmentationmodels To Identify Shared Copy Number Aberrations For Array Cgh Data, Veerabhadran Baladandayuthapani, Yuan Ji, Rajesh Talluri, Luis E. Nieto-Barajas, Jeffrey S. Morris
Bayesian Random Segmentationmodels To Identify Shared Copy Number Aberrations For Array Cgh Data, Veerabhadran Baladandayuthapani, Yuan Ji, Rajesh Talluri, Luis E. Nieto-Barajas, Jeffrey S. Morris
Jeffrey S. Morris
Array-based comparative genomic hybridization (aCGH) is a high-resolution high-throughput technique for studying the genetic basis of cancer. The resulting data consists of log fluorescence ratios as a function of the genomic DNA location and provides a cytogenetic representation of the relative DNA copy number variation. Analysis of such data typically involves estimation of the underlying copy number state at each location and segmenting regions of DNA with similar copy number states. Most current methods proceed by modeling a single sample/array at a time, and thus fail to borrow strength across multiple samples to infer shared regions of copy number aberrations. …
Participation And Engagement In Sport: A Double Hurdle Approach For The United Kingdom, Babatunde Buraimo, Brad Humphreys, Rob Simmons
Participation And Engagement In Sport: A Double Hurdle Approach For The United Kingdom, Babatunde Buraimo, Brad Humphreys, Rob Simmons
Dr Babatunde Buraimo
This paper uses pooled cross-section data from four waves of the United Kingdom’s Taking Part Survey, 2005 to 2009, in order to investigate determinants of probability of participation and levels of engagement in sports. The two rival modelling approaches considered here are the double-hurdle approach and the Heckman sample selection model. The Heckman model proves to be deficient in several key respects. The double-hurdle approach offers more reliable estimates than the Heckman sample selection model, at least for this particular survey. The distinction is more than just statistical nuance as there are substantive differences in qualitative results from the two …
Creation Of Synthetic Discrete Response Regression Models, Joseph Hilbe
Creation Of Synthetic Discrete Response Regression Models, Joseph Hilbe
Joseph M Hilbe
The development and use of synthetic regression models has proven to assist statisticians in better understanding bias in data, as well as how to best interpret various statistics associated with a modeling situation. In this article I present code that can be easily amended for the creation of synthetic binomial, count, and categorical response models. Parameters may be assigned to any number of predictors (which are shown as continuous, binary, or categorical), negative binomial heterogeneity parameters may be assigned, and the number of levels or cut points and values may be specified for ordered and unordered categorical response models. I …
Statistical Criteria For Selecting The Optimal Number Of Untreated Subjects Matched To Each Treated Subject When Using Many-To-One Matching On The Propensity Score, Peter C. Austin
Peter Austin
Propensity-score matching is increasingly being used to estimate the effects of treatments using observational data. In many-to-one (M:1) matching on the propensity score, M untreated subjects are matched to each treated subject using the propensity score. The authors used Monte Carlo simulations to examine the effect of the choice of M on the statistical performance of matched estimators. They considered matching 1–5 untreated subjects to each treated subject using both nearest-neighbor matching and caliper matching in 96 different scenarios. Increasing the number of untreated subjects matched to each treated subject tended to increase the bias in the estimated treatment effect; …
The Performance Of Different Propensity-Score Methods For Estimating Differences In Proportions (Risk Differences Or Absolute Risk Reductions) In Observational Studies, Peter C. Austin
Peter Austin
Propensity score methods are increasingly being used to estimate the effects of treatments on health outcomes using observational data. There are four methods for using the propensity score to estimate treatment effects: covariate adjustment using the propensity score, stratification on the propensity score, propensity-score matching, and inverse probability of treatment weighting (IPTW) using the propensity score. When outcomes are binary, the effect of treatment on the outcome can be described using odds ratios, relative risks, risk differences, or the number needed to treat. Several clinical commentators suggested that risk differences and numbers needed to treat are more meaningful for clinical …