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Search Results: 1 - 10 of 67036 matches for " non-parametric data analysis "
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A new approach for product cost estimation using data envelopment analysis
Fantahun M. Defersha,Adil Salam,Nadia Bhuiyan
International Journal of Industrial Engineering Computations , 2012,
Abstract: Cost estimation of new products has always been difficult as only few design, manufacturing and operational features will be known. In these situations, parametric or non-parametric methods are commonly used to estimate the cost of a product given the corresponding cost drivers. The parametric models use priori determined cost function where the parameters of the function are evaluated from historical data. Non-parametric methods, on the other hand, attempt to fit curves to the historic data without predetermined function. In both methods, it is assumed that the historic data used in the analysis is a true representation of the relation between the cost drivers and the corresponding costs. However, because of efficiency variations of the manufacturers and suppliers, changes in supplier selections, market fluctuations, and several other reasons, certain costs in the historic data may be too high whereas other costs may represent better deals for their corresponding cost drivers. Thus, it may be important to rank the historic data and identify benchmarks and estimate the target costs of the product based on these benchmarks. In this paper, a novel adaptation of cost drivers and cost data is introduced in order to use data envelopment analysis for the purpose of ranking cost data and identify benchmarks, and then estimate the target costs of a new product based on these benchmarks. An illustrative case study has been presented for the cost estimation of landing gears of an aircraft manufactured by an aerospace company located in Montreal, CANADA.
Trend Analysis of Precipitation in Some Selected Stations in Anambra State  [PDF]
A. Ifeka, A. Akinbobola
Atmospheric and Climate Sciences (ACS) , 2015, DOI: 10.4236/acs.2015.51001
Abstract: State is in the South East geopolitical zone of Nigeria. The major occupation of the people in this region is trading and farming, which depends on rainfall and other climatic factors. This paper presents statistical and trend analyses of the rainfall in some selected stations in Anambra State, which includes Ifite-Ogwari, Awka, Onitsha and Ihiala. Rainfall data for a period of 1971-2010 were obtained from Climate Research Unit (CRU). The existence of trend and statistical analyses was conducted on monthly total rainfalls using non-parametric techniques. The study revealed that overall averages of yearly and monthly total rainfall were 5798.78 mm and 1739.62 mm in Ifite-Ogwari, 6051.8 mm and 1815 mm in Awka, 6288.87 mm and 1886.88 mm in Onitsha, and 6637.19 mm and 1997.1 mm in Ihiala. Yearly total rainfall has Mann-Whitney of 26 and 41 between 1971 and 1990, 1991 and 2010 respectively in Ifite-Ogwari, 32 and 42 between 1971 and 1990, 1991 and 2010 respectively in Awka, 42 and 39 between 1971 and 1990, 1991 and 2010 respectively in Onitsha, and 33 and 45 between 1971 and 1990, 1991 and 2010 respectively in Ihiala. These parameters show that there are significant trends in the rainfall in term of yearly total for the period. Sen’s estimator revealed that there were significant downward trends for yearly total (-0.775 mm/year) and (-0.094 mm/year) within the period of 1971-1990 and 1991-2010 in Ifite-Ogwari. There was an upward trend of yearly total (1.841 mm/year) between 1971 and1990, whereas there was a downward trend of yearly total (-0.211) between 1991 and 2010 in Awka. It was concluded that there was a significant downward trend in the yearly total and mean rainfalls in Ifite-Ogwari, Awka, Onitsha and Ihiala in the last four decades (40 years), which could be attributed to climate change.
Application of Non-parametric Analysis Technique amongst Postgraduate Education Research: A Survey of South African Universities
Anass BAYAGA,Liile Lerato LEKENA
Journal of International Social Research , 2010,
Abstract: The objective of this research was to determine factors that influence application of non-parametric analysis technique. The data emanated from research done by postgraduate students over a ten year period (1995-2004) and archived by the project in postgraduate education research (PPER). A Survey of three South African universities was conducted. The classification of researches from chosen prominent universities were made by research title, research topic, target population, data collection method, and other diversity titles which were used to map the position of non parametric analysis. The sample in the three (3) universities included four hundred and twenty-one (421) sampled researches.The first finding indicated that the data presentation chapters of the sampled researches were all analysed using descriptive analysis without application of non-parametric technique. Thus, no sampled research applied non-parametric analysis technique. Secondly, the findings suggested that there was a relationship between research title and data analysis technique. Thirdly, there was association between research titles and target populations, which consequently influence choice of data analysis. Lastly, the dominant themes amongst the sampled researches were age, inclusive education and education.
Efficiency of Generation Companies in the Deregulated Electricity Market of Singapore: Parametric and Non-Parametric Approaches
Youngho Chang,Wai Lit Toh
International Journal of Electronic Business Management , 2007,
Abstract: This study examines the technical efficiency of the electricity generation companies in a deregulated electricity market. Two approaches are used – parametric and non-parametric. Parametric models show that there exist high levels of efficiency among the generation firms; the lowest score is 99.83%, after accounting for noise. While non-parametric models do not give efficiency scores as high as those from the parametric models, the lowest is still 89.75%, which is considerably high. Although the correlation of efficiency results from both types of models is poor, the generation firms have considerably high efficiency levels in each model. In addition, non-parametric models have given insight on how firms could improve their efficiency by such a way that it replicates the input combinations of the efficient benchmark firm(s).
Adaptive basis selection for functional data analysis via stochastic penalization
Anselmo, Cezar A.F.;Dias, Ronaldo;Garcia, Nancy L.;
Computational & Applied Mathematics , 2005, DOI: 10.1590/S0101-82052005000200004
Abstract: we propose an adaptive method of analyzing a collection of curves which can be, individually, modeled as a linear combination of spline basis functions. through the introduction of latent bernoulli variables, the number of basis functions, the variance of the error measurements and the coefficients of the expansion are determined. we provide a modification of the stochastic em algorithm for which numerical results show that the estimates are very close to the true curve in the sense of l2 norm.
Adaptive basis selection for functional data analysis via stochastic penalization
Cezar A.F. Anselmo,Ronaldo Dias,Nancy L. Garcia
Computational and Applied Mathematics , 2005,
Abstract: We propose an adaptive method of analyzing a collection of curves which can be, individually, modeled as a linear combination of spline basis functions. Through the introduction of latent Bernoulli variables, the number of basis functions, the variance of the error measurements and the coefficients of the expansion are determined. We provide a modification of the stochastic EM algorithm for which numerical results show that the estimates are very close to the true curve in the sense of L2 norm.
Effects of Ownership on Hospital Efficiency in Germany
Oliver Tiemann,Jonas Schrey?gg
BuR : Business Research , 2009,
Abstract: The objective of our study was to evaluate the efficiency of public, private for-profit, and private non-profit hospitals in Germany. First, bootstrapped data envelopment analysis (DEA) was used to evaluate the efficiency of a panel (n = 1,046) of public, private for-profit, and private non-profit hospitals between 2002 and 2006. This was followed by a second-step truncated linear regression model with bootstrapped DEA efficiency scores as dependent variable. The results show that public hospitals performed significantly better than their private for-profit and non-profit counterparts. In addition, we found a significant positive association between hospital size and efficiency, and that competitive pressure had a significant negative impact on hospital efficiency.
Nelson-Aalen and Kaplan-Meier Estimators in Competing Risks  [PDF]
Didier Alain Njamen-Njomen, Joseph Ngatchou-Wandji
Applied Mathematics (AM) , 2014, DOI: 10.4236/am.2014.54073
Abstract:

In this paper, stochastic processes developed by Aalen [1] [2] are adapted to the Nelson-Aalen and Kaplan-Meier [3] estimators in a context of competing risks. We focus only on the probability distributions of complete downtime individuals whose causes are known and which bring us to consider a partition of individuals into sub-groups for each cause. We then study the asymptotic properties of nonparametric estimators obtained.


Diferentes métodos estadísticos para el análisis de variables discretas. Una aplicación en las ciencias agrícolas y técnicas
Herrera Villafranca,Magaly; Guerra Bustillos,Caridad W; Sarduy García,Lucía; García Hernández,Yoleisy; Martínez,Carlos Enrique;
Revista Ciencias T??cnicas Agropecuarias , 2012,
Abstract: the objective of this article was to evaluate three different statistical methods to conduct analyses of discrete variables. the information came from an experiment developed at the camilo cienfuegos genetics enterprise in the pinar del río province in 2007-2008 related to the ct-115 forrage production. a complete randomized design was used with three treatments and ten repetitions. the variables analysed were: number of stems, number of sprouts, total number of leaves/stem, total number of leaves/sprout, number of dried leaves/stem and number of dried leaves/sprouts. the parametric variance analysis and its homologous non-parametric, kruskal-wallis test and the generalized lineal model were taken into account. the theoretical assumptions of the variance analyses to the test error normality were verified. the shapiro wilk test, kolmogorov smirnov and the lilliefors test were used, shapiro wilk test was the most robust to detect lack of normality. for the variance homogeneity, the bartlett and levene test were used both with similar results. the variables were transformed with the square root transformation which did not improve the normal distribution adjustment to the variable number of dried leaves/sprout. the probability values maintained the same outcomes respect to ho tests for the non-parametric test, compared with its homologous parametric f from fisher test. the criteria of goodness of fit in the generalized linear model permitted evaluating the best adjustment effects. it was considered that this model is more flexible than the parametric variance analyses because the variables under study did not require the theoretical assumptions fulfilment.
ks: Kernel Density Estimation and Kernel Discriminant Analysis for Multivariate Data in R
Tarn Duong
Journal of Statistical Software , 2007,
Abstract: Kernel smoothing is one of the most widely used non-parametric data smoothing techniques. We introduce a new R package ks for multivariate kernel smoothing. Currently it contains functionality for kernel density estimation and kernel discriminant analysis. It is a comprehensive package for bandwidth matrix selection, implementing a wide range of data-driven diagonal and unconstrained bandwidth selectors.
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