Canonical correlation analysis and DEA for azorean agriculture efficiency

In this paper we will document the application of canonical correlation analysis to variable aggregation using the correlations of the original variables with the canonical variates. A case study, about farms in Terceira Island, with a small data set is presented. In this data set of 30 farms we intend to use 17 input variables and 2 output variables to measure DEA efficiency. Without any data reduction procedure several problems known as “curse of dimensionality” are expected. With the data reduction procedures suggested it was possible to conclude quite acceptable and domain consistent conclusions.N/

Azorean agriculture efficiency by PAR

The producers always aspire at increasing the efficiency of their production process. However, they do not always succeed in optimizing their production. In the last years, the interest on Data Envelopment Analysis (DEA) as a powerful tool for measuring efficiency has increased. This is due to the large amount of data sets collected to better understand the phenomena under study, and, at the same time, to the need of timely and inexpensive information. The “Productivity Analysis with R” (PAR) framework establishes a user-friendly data envelopment analysis environment with special emphasis on variable selection and aggregation, and summarization and interpretation of the results. The starting point is the following R packages: DEA (Diaz-Martinez and Fernandez-Menendez, 2008) and FEAR (Wilson, 2007). The DEA package performs some models of Data Envelopment Analysis presented in (Cooper et al., 2007). FEAR is a software package for computing nonparametric efficiency estimates and testing hypotheses in frontier models. FEAR implements the bootstrap methods described in (Simar and Wilson, 2000). PAR is a software framework using a portfolio of models for efficiency estimation and providing also results explanation functionality. PAR framework has been developed to distinguish between efficient and inefficient observations and to explicitly advise the producers about possibilities for production optimization. PER framework offers several R functions for a reasonable interpretation of the data analysis results and text presentation of the obtained information. The output of an efficiency study with PAR software is self- explanatory. We are applying PAR framework to estimate the efficiency of the agricultural system in Azores (Mendes et al., 2009). All Azorean farms will be clustered into homogeneous groups according to their efficiency measurements to define clusters of “good” practices and cluster of “less good” practices. This makes PAR appropriate to support public policies in agriculture sector in Azores.N/

The interactive technologies as a component of a supporting educational environment on university

W artykule przedstawiono zastosowanie technologii interaktywnych w kształceniu uniwersyteckim jako wsparcie procesu edukacyjnego, wnioski z analizy uwarunkowań kształcenia, które przyczyniają się do tworzenia środowiska wspierającegoIn the article the interactive technologies are revealed in the terms of the university education. The aspects of this phenomenon as a component of a supporting educational environment. Analysis of the results of the research and approbation of the model makes it possible to draw conclusions about pedagogical conditions the presence of which contributes to the provision of a supporting environmen

A statistical test vs. a validation experiment in Gene Expression Study

Report published in the Proceedings of the National Conference on "Education and Research in the Information Society", Plovdiv, May, 2014Comparative CT Method compares the Ct value of one target gene to another using the formula called 2-ΔΔCT. To make this method valid, the efficiency of the target amplification (the gene of interest) and the efficiency of the reference amplification (the endogenous control) must be equal. In this article we propose to test statistical hypotheses instead to perform validation biological experiments when we want to show that the efficiencies of the target and endogenous control amplifications are approximately equal.Association for the Development of the Information Society, Institute of Mathematics and Informatics Bulgarian Academy of Sciences, Plovdiv University "Paisii Hilendarski

Extraction of Fraud Schemes from Trade Series

2000 Mathematics Subject Classification: 62H30, 62M10, 62M20, 62P20, 94A13.It is very often the case that the patterns of a fraudulent activity in trade are hidden within existing trade data time series. Furthermore, with the advent of powerful and affordable computing hardware, relatively big amounts of available trade data can be quickly analyzed with a view to assisting antifraud investigations in this field. In this paper, based on the availability of such import/export data series, we present a statistical method for the identification of potential fraud schemes, by extracting and highlighting those cases which lend themselves to further investigation by anti-fraud domain experts. The proposed method consists in applying time series analysis for prediction purposes, calculating the resulting significant deviations, and finally clustering time series with similar patterns together, thus identifying suspect or abnormal cases

Knowledge Presentation and Reasoning with Loglinear Models

Our approach for knowledge presentation is based on the idea of expert system shell. At first we will build a graph shell of both possible dependencies and possible actions. Then, reasoning by means of Loglinear models, we will activate some nodes and some directed links. In this way a Bayesian network and networks presenting loglinear models are generated

Canonical Correlation Analysis in Variable Aggregation in DEA.

14º Congresso da APDIO, 7 a 9 de Setembro de 2009, Faculdade de Ciências e Tecnologia - Caparica.Neste trabalho documenta-se a aplicação de análise de correlações canónicas à agregação de variáveis em DEA, usando as correlações entre as variáveis originais e os componentes canónicos extraídos. É apresentado um caso de estudo que utiliza um pequeno conjunto de dados sobre explorações agrícolas na ilha terceira. Neste conjunto de 30 explorações agrícolas pretende-se usar 17 variáveis de input e 2 de output para avaliar a eficiência usando DEA. Sem qualquer redução de dados, vários problemas conhecidos como "praga da dimensionalidade" seriam esperados. Com os procedimentos sugeridos foi possível obter resultados razoáveis e de acordo com o conhecimento de domínio actual.ABSTRACT: In this paper we will document the application of canonical correlation analysis to variable aggregation using the correlations of the original variables with the canonical variates. A case study, about farms in Terceira Island, with a small data set is presented. In this data set of 30 farms we intend to use 17 input variables and 2 output variables to measure DEA efficiency. Without any data reduction procedure several problems known as "curse of dimensionality" are expected. With the data reduction procedures suggested it was possible to conclude quite acceptable and domain consistent conclusions

An Approach to Variable Aggregation in Efficiency Analysis

Conference: The paper is selected from International Conference "Classification, Forecasting, Data Mining" CFDM 2009, Varna, Bulgaria, June-July 2009.In the nonparametric framework of Data Envelopment Analysis the statistical properties of its estimators have been investigated and only asymptotic results are available. For DEA estimators results of practical use have been proved only for the case of one input and one output. However, in the real world problems the production process is usually well described by many variables. In this paper a machine learning approach to variable aggregation based on Canonical Correlation Analysis is presented. This approach is applied for efficiency estimation of all the farms in Terceira Island of the Azorean archipelago

A software framework for measuring efficiency.

Trabalho apresentado em UseR Conference, Rennes, França, Julho 8 a 10 de 2009."[...]. PAR is a software framework using a variety of models estimating efficiency and providing results explanation functionality. [...]. We are applying PAR framework to estimate the efficiency of the agricultural system in Azores [Mendes et al., 2009]. All Azorean farms will be clustered into homogeneous groups according to their efficiency measurements to define clusters of "good" practices and cluster of "less good" practices. This makes PAR appropriate to support public policies in agriculture sector in Azores. [...]"This work has been partially supported by Regional Directorate for Science and Technology of Azores Government through the project M.2.1.2/l/009/2008, "Productivity Analysis of Azorean Cattle-Breeding Farms with R Statistical Software"

An Approach to Variable Aggregation in Efficiency Analysis

In the nonparametric framework of Data Envelopment Analysis the statistical properties of its estimators have been investigated and only asymptotic results are available. For DEA estimators results of practical use have been proved only for the case of one input and one output. However, in the real world problems the production process is usually well described by many variables. In this paper a machine learning approach to variable aggregation based on Canonical Correlation Analysis is presented. This approach is applied for efficiency estimation of all the farms in Terceira Island of the Azorean archipelago