Open Access. Powered by Scholars. Published by Universities.®
Other Statistics and Probability Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Keyword
-
- Bayes action (1)
- Biofuel (1)
- Cholesterol (1)
- Cigarette flavoring; every day smoker; national survey; population-based study; smoking behaviors; smoking status (1)
- Complex genetic traits (1)
-
- Corn residue removal (1)
- Cross-validation (1)
- Epistasis (1)
- FDA (1)
- Gene Expression (1)
- Genetics (1)
- Genomic prediction (1)
- ICH Q1A/Q1E (1)
- Machine learning (1)
- Managing risk. (1)
- Mixed models (1)
- Optimization constrains. (1)
- Perennial warm-season grass (1)
- Prediction (1)
- Problem classes (1)
- Shelf life estimation (1)
- Soil organic carbon. (1)
- Soil properties (1)
- Stability (1)
- Stacking (1)
- Transcription (1)
Articles 1 - 10 of 10
Full-Text Articles in Other Statistics and Probability
Heterogeneity Aware Random Forest For Drug Sensitivity Prediction, Raziur Rahman, Kevin Matlock, Souparno Ghosh, Ranadip Pal
Heterogeneity Aware Random Forest For Drug Sensitivity Prediction, Raziur Rahman, Kevin Matlock, Souparno Ghosh, Ranadip Pal
Department of Statistics: Faculty Publications
Samples collected in pharmacogenomics databases typically belong to various cancer types. For designing a drug sensitivity predictive model from such a database, a natural question arises whether a model trained on diverse inter-tumor heterogeneous samples will perform similar to a predictive model that takes into consideration the heterogeneity of the samples in model training and prediction. We explore this hypothesis and observe that ensemble model predictions obtained when cancer type is known out-perform predictions when that information is withheld even when the samples sizes for the former is considerably lower than the combined sample size. To incorporate the heterogeneity idea …
Assessing The Impact Of Retreat Mechanisms In A Simple Antarctic Ice Sheet Model Using Bayesian Calibration, Kelsey L. Ruckert, Gary Shaffer, David Pollard, Yawen Guan, Tony E. Wong, Chris E. Forest, Klaus Keller
Assessing The Impact Of Retreat Mechanisms In A Simple Antarctic Ice Sheet Model Using Bayesian Calibration, Kelsey L. Ruckert, Gary Shaffer, David Pollard, Yawen Guan, Tony E. Wong, Chris E. Forest, Klaus Keller
Department of Statistics: Faculty Publications
The response of the Antarctic ice sheet (AIS) to changing climate forcings is an important driver of sea-level changes. Anthropogenic climate change may drive a sizeable AIS tipping point response with subsequent increases in coastal flooding risks. Many studies analyzing flood risks use simple models to project the future responses of AIS and its sea-level contributions. These analyses have provided important new insights, but they are often silent on the effects of potentially important processes such as Marine Ice Sheet Instability (MISI) or Marine Ice Cliff Instability (MICI). These approximations can be well justified and result in more parsimonious and …
Perennial Warm-Season Grasses For Producing Biofuel And Enhancing Soil Properties: An Alternative To Corn Residue Removal, Humberto Blanco-Canqui, Robert B. Mitchell, Virginia L. Jin, Marty R. Schmer, Kent M. Eskridge
Perennial Warm-Season Grasses For Producing Biofuel And Enhancing Soil Properties: An Alternative To Corn Residue Removal, Humberto Blanco-Canqui, Robert B. Mitchell, Virginia L. Jin, Marty R. Schmer, Kent M. Eskridge
Department of Statistics: Faculty Publications
Removal of corn (Zea mays L.) residues at high rates for biofuel and other off-farm uses may negatively impact soil and the environment in the long term. Biomass removal from perennial warm-season grasses (WSGs) grown in marginally-productive lands could be an alternative to corn residue removal as biofuel feedstocks while controlling water and wind erosion, sequestering carbon (C), cycling water and nutrients, and enhancing other soil ecosystem services. We compared wind and water erosion potential, soil compaction, soil hydraulic properties, soil organic C (SOC), and soil fertility between biomass removal from WSGs and corn residue removal from rainfed no-till …
Impact Of Menthol Smoking On Nicotine Dependence For Diverse Racial/Ethnic Groups Of Daily Smokers, Julia N. Soulakova, Ryan R. Danczak
Impact Of Menthol Smoking On Nicotine Dependence For Diverse Racial/Ethnic Groups Of Daily Smokers, Julia N. Soulakova, Ryan R. Danczak
Department of Statistics: Faculty Publications
Introduction: The aims of this study were to evaluate whether menthol smoking and race/ethnicity are associated with nicotine dependence in daily smokers. Methods: The study used two subsamples of U.S. daily smokers who responded to the 2010–2011 Tobacco Use Supplement to the Current Population Survey. The larger subsample consisted of 18,849 non-Hispanic White (NHW), non-Hispanic Black (NHB), and Hispanic (HISP) smokers. The smaller subsample consisted of 1112 non-Hispanic American Indian/Alaska Native (AIAN), non-Hispanic Asian (ASIAN), non-Hispanic Hawaiian/Pacific Islander (HPI), and non-Hispanic Multiracial (MULT) smokers. Results: For larger (smaller) groups the rates were 45% (33%) for heavy smoking (16+ cig/day), 59% …
Evaluating Current Practices In Shelf Life Estimation, Robert Capen, David Christopher, Patrick Forenzo, Kim Huynh-Ba, David Leblond, Oscar Liu, John O'Neill, Nate Patterson, Michelle Quinlan, Radhika Rajagopalan, James Schwenke, Walter W. Stroup
Evaluating Current Practices In Shelf Life Estimation, Robert Capen, David Christopher, Patrick Forenzo, Kim Huynh-Ba, David Leblond, Oscar Liu, John O'Neill, Nate Patterson, Michelle Quinlan, Radhika Rajagopalan, James Schwenke, Walter W. Stroup
Department of Statistics: Faculty Publications
The current International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH) methods for determining the supported shelf life of a drug product, described in ICH guidance documents Q1A and Q1E, are evaluated in this paper. To support this evaluation, an industry data set is used which is comprised of 26 individual stability batches of a common drug product where most batches are measured over a 24 month storage period. Using randomly sampled sets of 3 or 6 batches from the industry data set, the current ICH methods are assessed from three perspectives. First, the distributional properties …
Generalized Confidence Intervals Compatible With The Min Test For Simultaneous Comparisons Of One Subpopulation To Several Other Subpopulations, Julia N. Soulakova
Generalized Confidence Intervals Compatible With The Min Test For Simultaneous Comparisons Of One Subpopulation To Several Other Subpopulations, Julia N. Soulakova
Department of Statistics: Faculty Publications
A problem where one subpopulation is compared to several other subpopulations in terms of means with the goal of estimating the smallest difference between the means commonly arises in biology, medicine, and many other scientific fields. A generalization of Strassburger, Bretz and Hochberg (2004) approach for two comparisons is presented for cases with three and more comparisons. The method allows constructing an interval-estimator for the smallest mean difference, which is compatible with the Min test. An application to a fluency-disorder study is illustrated. Simulations confirmed adequate probability coverage for normally distributed outcomes for a number of designs.
Increasing Genomic-Enabled Prediction Accuracy By Modeling Genotype X Environment Interactions In Kansas Wheat, Diego Jarquin, Cristiano Lemas Da Silva, R. Chris Gaynor, Jesse Poland, Allan Fritz, Reka Howard, Sarah Battenfield, José Crossa
Increasing Genomic-Enabled Prediction Accuracy By Modeling Genotype X Environment Interactions In Kansas Wheat, Diego Jarquin, Cristiano Lemas Da Silva, R. Chris Gaynor, Jesse Poland, Allan Fritz, Reka Howard, Sarah Battenfield, José Crossa
Department of Statistics: Faculty Publications
Wheat (Triticum aestivum L.) breeding programs test experimental lines in multiple locations over multiple years to get an accurate assessment of grain yield and yield stability. Selections in early generations of the breeding pipeline are based on information from only one or few locations and thus materials are advanced with little knowledge of the genotype × environment interaction (G × E) effects. Later, large trials are conducted in several locations to assess the performance of more advanced lines across environments. Genomic selection (GS) models that include G × E covariates allow us to borrow information not only from related …
Application Of Response Surface Methods To Determine Conditions For Optimal Genomic Prediction, Reka Howard, Alicia L. Carriquiry, William D. Beavis
Application Of Response Surface Methods To Determine Conditions For Optimal Genomic Prediction, Reka Howard, Alicia L. Carriquiry, William D. Beavis
Department of Statistics: Faculty Publications
An epistatic genetic architecture can have a significant impact on prediction accuracies of genomic prediction (GP) methods. Machine learning methods predict traits comprised of epistatic genetic architectures more accurately than statistical methods based on additive mixed linear models. The differences between these types of GP methods suggest a diagnostic for revealing genetic architectures underlying traits of interest. In addition to genetic architecture, the performance of GP methods may be influenced by the sample size of the training population, the number of QTL, and the proportion of phenotypic variability due to genotypic variability (heritability). Possible values for these factors and the …
Trans-Ancestry Fine Mapping And Molecular Assays Identify Regulatory Variants At The Angptl8 Hdl-C Gwas Locus, Maren E. Cannon, Qing Duan, Ying Wu, Monica Zeynalzadeh, Zheng Xu, Antti J. Kangas, Pasi Soininen, Mika Ala-Korpela, Mete Civelek, Aldons J. Lusis, Johanna Kuusisto, Francis S. Collins, Michael Boehnke, Hua Tang, Markku Laakso, Yun Li, Karen L. Mohlke
Trans-Ancestry Fine Mapping And Molecular Assays Identify Regulatory Variants At The Angptl8 Hdl-C Gwas Locus, Maren E. Cannon, Qing Duan, Ying Wu, Monica Zeynalzadeh, Zheng Xu, Antti J. Kangas, Pasi Soininen, Mika Ala-Korpela, Mete Civelek, Aldons J. Lusis, Johanna Kuusisto, Francis S. Collins, Michael Boehnke, Hua Tang, Markku Laakso, Yun Li, Karen L. Mohlke
Department of Statistics: Faculty Publications
Recent genome-wide association studies (GWAS) have identified variants associated with highdensity lipoprotein cholesterol (HDL-C) located in or near the ANGPTL8 gene. Given the extensive sharing of GWAS loci across populations, we hypothesized that at least one shared variant at this locus affects HDL-C. The HDL-C–associated variants are coincident with expression quantitative trait loci for ANGPTL8 and DOCK6 in subcutaneous adipose tissue; however, only ANGPTL8 expression levels are associated with HDL-C levels. We identified a 400-bp promoter region of ANGPTL8 and enhancer regions within 5 kb that contribute to regulating expression in liver and adipose. To identify variants functionally responsible for …
A Bayes Interpretation Of Stacking For M-Complete And M-Open Settings, Tri Le, Bertrand S. Clarke
A Bayes Interpretation Of Stacking For M-Complete And M-Open Settings, Tri Le, Bertrand S. Clarke
Department of Statistics: Faculty Publications
In M-open problems where no true model can be conceptualized, it is common to back off from modeling and merely seek good prediction. Even in M-complete problems, taking a predictive approach can be very useful. Stacking is a model averaging procedure that gives a composite predictor by combining individual predictors from a list of models using weights that optimize a cross validation criterion. We show that the stacking weights also asymptotically minimize a posterior expected loss. Hence we formally provide a Bayesian justification for cross-validation. Often the weights are constrained to be positive and sum to one. For greater generality, …