Search
Search Results
-
Bayesian Scan Statistics
In this chapter we describe Bayesian scan statistics, a class of methods which build both on the prior literature on scan statistics and on Bayesian...
-
Adaptive Likelihood Ratio Scans for the Detection of Space-Time Clusters
This work presents a methodology to detect space-time clusters, based on adaptive likelihood ratios (ALRs), which preserves the martingale structure...
-
Adaptive Generalized Logistic Lasso and Its Application to Rankings in Sports
The generalized lasso is a popular model for ranking competitors, as it allows for implicit grou** of estimated abilities. In this work, we present...
-
Inference for Quasi-reaction Models with Covariate-Dependent Rates
Statistical models of quasi-reaction systems are typically described by constant reaction rates. This assumption is too restrictive in many...
-
Gene Coexpression Analysis with Dirichlet Mixture Model: Accelerating Model Evaluation Through Closed-Form KL Divergence Approximation Using Variational Techniques
Gene coexpression analysis poses unique challenges, particularly in clustering normalized gene profiles where dedicated algorithms are lacking....
-
REML for Two-Dimensional P-Splines
We propose a new method based on residual (or restricted) maximum likelihood (REML) for P-splines. Existing methods use a transformation of P-splines...
-
Bayesian Approaches to Model Overdispersion in Spatio-Temporal Binomial Data
In this work, we introduce a direct spatio-temporal extension of the spatial conditional overdispersion models for binomially distributed response...
-
Additive Mixed Models for Location, Scale and Shape via Gradient Boosting Techniques
In this work we adapt recent findings from statistical boosting in order to construct an estimation approach for distributional regression including...
-
Learning Bayesian Networks from Ordinal Data - The Bayesian Way
We propose a new Bayesian method for Bayesian network structure learning from ordinal data. Our Bayesian method is similar to a recently proposed...
-
Regression Analysis with Missing Data Using Interval Imputation
Regression analysis with missing data is a common problem in statistical modelling. Majority of the available methods use point imputation strategy...
-
Optimism Correction of the AUC with Complex Survey Data
Special statistical techniques are required to develop valid prediction models for complex survey data. Recently, a weighted estimator has been...
-
Statistical Models for Patient-Centered Outcomes in Clinical Studies
Days alive and out of hospital is recommended as a patient-centered outcome in perioperative clinical studies. It is defined as the number of days,...
-
LINGO Programs Usage and New Facts by Iris Data
This chapter introduces four LINGO Programs and new facts from Fisher’s Iris data. It consists of three species, Setosa (G1), Versicolor (G2), and...
-
Swiss Banknote Data and CPD Data: The Essence of Discriminant Theory
We show two results of Swiss banknote data (200 * 6) and CPD (Cephalo-pelvic Disproportion) data (19 * 240) explaining the important roles of...
-
Three Important Studies for Cancer Gene Diagnosis
This Chapter introduces three studies to confirm the correctness of cancer patients’ design three principles using four different sizes of...
-
Two-Step Practical Screening Method for Cancer Gene Diagnoses—Multivariate Oncogenes Among 169 Microarrays
If physicians analyze their microarrays or RNA by my practical 2-step screening method (Method3), they obtain many “vital BGSs with a few genes and...
-
Nearest Neighbors of Multivariate Runs
We investigate the joint distributions of the number of nearest neighbor contacts between different objects in the context of runs-related statistics...
-
Graphing Methods
This chapter considers graphing methods to illustrate some of the results forthcoming from the 2 × 2 contingency tableContingency table, in...
-
Paired Complementary Measures
This chapter considers complementary paired measures of discrimination which can be derived from the 2 × 2 contingency tableContingency table,...
-
Classification of Metrics of Binary Classification
By way of conclusion, this chapter looks at possible ways to classify the various measures of binary classification which have been detailed in the...