Displaying similar documents to “Principal component analysis for functional data on grain yield of winter wheat cultivars”

Analysis of multivariate repeated measures data using a MANOVA model and principal components

Mirosław Krzysko, Tadeusz Smiałowski, Waldemar Wołynski (2014)

Biometrical Letters

Similarity:

In this paper we consider a set of T repeated measurements on p characteristics on each of n individuals. The n individuals themselves may be divided and randomly assigned to K groups. These data are analyzed using a mixed effect MANOVA model, assuming that the data on an individual have a covariance matrix which is a Kronecker product of two positive definite matrices. Results are illustrated on a data set obtained from experiments with varieties of winter rye.

Canonical correlation analysis for functional data

Mirosław Krzyśko, Łukasz Waszak (2013)

Biometrical Letters

Similarity:

Classical canonical correlation analysis seeks the associations between two data sets, i.e. it searches for linear combinations of the original variables having maximal correlation. Our task is to maximize this correlation, and is equivalent to solving a generalized eigenvalue problem. The maximal correlation coefficient (being a solution of this problem) is the first canonical correlation coefficient. In this paper we propose a new method of constructing canonical correlations and canonical...

Towards Reverse Engineering of PDF Documents

Baker, Josef B., Sexton, Alan P., Sorge, Volker

Similarity:

We present a progress report on our ongoing project of reverse engineering scientific PDF documents. The aim is to obtain mathematical markup that can be used as source for regenerating a document that resembles the original as closely as possible. This source can then be a basis for further document processing. Our current tool uses specialised PDF extraction together with image analysis to produce near perfect input for parsing mathematical formula. Applying a linear grammar and specific...

Selection of variables in Discrete Discriminant Analysis

Anabela Marques, Ana Sousa Ferreira, Margarida G.M.S. Cardoso (2013)

Biometrical Letters

Similarity:

In Discrete Discriminant Analysis one often has to deal with dimensionality problems. In fact, even a moderate number of explanatory variables leads to an enormous number of possible states (outcomes) when compared to the number of objects under study, as occurs particularly in the social sciences, humanities and health-related elds. As a consequence, classi cation or discriminant models may exhibit poor performance due to the large number of parameters to be estimated. In the present...

Towards a Flexible Author Name Disambiguation Framework

Bolikowski, Łukasz, Dendek, Piotr Jan

Similarity:

In this paper we propose a flexible, modular framework for author name disambiguation. Our solution consists of the core which orchestrates the disambiguation process, and replaceable modules performing concrete tasks. The approach is suitable for distributed computing, in particular it maps well to the MapReduce framework. We describe each component in detail and discuss possible alternatives. Finally, we propose procedures for calibration and evaluation of the described system. ...

Analysis and Data Mining of Lead-Zinc Ore Data

Zanev, Vladimir, Topalov, Stanislav, Christov, Veselin (2013)

Serdica Journal of Computing

Similarity:

This paper presents the results of our data mining study of Pb-Zn (lead-zinc) ore assay records from a mine enterprise in Bulgaria. We examined the dataset, cleaned outliers, visualized the data, and created dataset statistics. A Pb-Zn cluster data mining model was created for segmentation and prediction of Pb-Zn ore assay data. The Pb-Zn cluster data model consists of five clusters and DMX queries. We analyzed the Pb-Zn cluster content, size, structure, and characteristics. The set...