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- Malgorzata Bogdan, Jayanta K Ghosh, R W Doerge
- Genetics
- 2004

The problem of locating multiple interacting quantitative trait loci (QTL) can be addressed as a multiple regression problem, with marker genotypes being the regressor variables. An important and difficult part in fitting such a regression model is the estimation of the QTL number and respective interactions. Among the many model selection criteria that can… (More)

- M Bogdan, R W Doerge
- Heredity
- 2005

In many empirical studies, it has been observed that genome scans yield biased estimates of heritability, as well as genetic effects. It is widely accepted that quantitative trait locus (QTL) mapping is a model selection procedure, and that the overestimation of genetic effects is the result of using the same data for model selection as estimation of… (More)

- Andreas Baierl, Andreas Futschik, Malgorzata Bogdan, Przemyslaw Biecek
- Computational Statistics & Data Analysis
- 2007

One of the most popular criteria for model selection is the Bayesian Information Criterion (BIC). It is based on an asymptotic approximation using Bayes rule when the sample size tends to infinity and the dimension of the model is fixed. Although it works well in classical applications, it performs less satisfactorily for high dimensional problems, i.e.… (More)

- Florian Frommlet, Andreas Futschik, Malgorzata Bogdan
- Bioinformatics
- 2004

MOTIVATION
Pairwise local sequence alignment is commonly used to search data bases for sequences related to some query sequence. Alignments are obtained using a scoring matrix that takes into account the different frequencies of occurrence of the various types of amino acid substitutions. Software like BLAST provides the user with a set of scoring matrices… (More)

- Florian Frommlet, Felix Ruhaltinger, Piotr Twaróg, Malgorzata Bogdan
- Computational Statistics & Data Analysis
- 2012

- Malgorzata Bogdan, Jayanta K. Ghosh, Aleksandra Ochman, Surya T. Tokdar
- Quality and Reliability Eng. Int.
- 2007

- Malgorzata Bogdan, Jayanta K. Ghosh, Malgorzata Zak-Szatkowska
- Quality and Reliability Eng. Int.
- 2008

We consider the situation when a large data base needs to be searched to identify a few important predictors of a given quantitative response variable. There is a lot of evidence that in this case classical model selection criteria, like Akaike Information Criterion (AIC) or Bayesian Information Criterion (BIC), have a strong tendency to overestimate the… (More)

- Weijie Su, Malgorzata Bogdan, Emmanuel J. Candès
- ArXiv
- 2015

In regression settings where explanatory variables have very low correlations and where there are relatively few effects each of large magnitude, it is commonly believed that the Lasso shall be able to find the important variables with few errors—if any. In contrast, this paper shows that this is not the case even when the design variables are… (More)

- Vinzenz Erhardt, Malgorzata Bogdan, Claudia Czado
- Statistical applications in genetics and…
- 2010

We consider the problem of locating multiple interacting quantitative trait loci (QTL) influencing traits measured in counts. In many applications the distribution of the count variable has a spike at zero. Zero-inflated generalized Poisson regression (ZIGPR) allows for an additional probability mass at zero and hence an improvement in the detection of… (More)

With the rise of both the number and the complexity of traits of interest, control of the false discovery rate (FDR) in genetic association studies has become an increasingly appealing and accepted target for multiple comparison adjustment. While a number of robust FDR-controlling strategies exist, the nature of this error rate is intimately tied to the… (More)