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Search Results: 1 - 10 of 45247 matches for " multiple discriminant analysis "
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Comparación entre tres técnicas de clasificación
Revista Colombiana de Estadística , 2009,
Abstract: in this paper we show the results of a comparison simulation study for three classification techniques: multinomial logistic regression (mlr), no metric discriminant analysis (nda) and linear discriminant analysis (lda). the measure used to compare the performance of the three techniques was the error classification rate (ecr). we found that mlr and lda techniques have similar performance and that they are better than dna when the population multivariate distribution is normal or logit-normal. for the case of log-normal and sinh-1-normal multivariate distributions we found that mlr had the better performance.
Hernández Barajas Freddy,Correa Morales Juan Carlos
Revista Colombiana de Estadística , 2009,
Abstract: In this paper we show the results of a comparison simulation study for three classification techniques: Multinomial Logistic Regression (MLR), No Metric Discriminant Analysis (NDA) and Linear Discriminant Analysis (LDA). The measure used to compare the performance of the three techniques was the Error Classification Rate (ECR). We found that MLR and LDA techniques have similar performance and that they are better than DNA when the population multivariate distribution is Normal or Logit-Normal. For the case of log-normal and Sinh^{ 1}-normal multivariate distributions we found that MLR had the better performance. En este artículo se muestran los resultados de un estudio de comparación mediante simulación de tres técnicas de clasificación, regresión logística multinomial (MLR), análisis discriminante no métrico (NDA) y análisis discriminante lineal (LDA). El desempe o de las técnicas se midió usando la tasa de clasificación errónea. Se encontró que las técnicas MLR y LDA tuvieron un desempe o similar y muy superior a NDA cuando la distribución multivariada de las poblaciones es normal o logit-normal; en el caso de distribuciones multivariadas log-normal y Sinh^{ 1}-normal la técnica MLR tuvo mejor desempe o.
Phytosociological Study in Quercus libani Oliv.’s Site by Analyzing Environmental Factors in West Azerbaijan, Iran
Raza Basiri
Journal of Applied Sciences , 2010,
Abstract: In this study, Quercus libani Oliv.’s site in Sardasht has been studied phytosociologically. The vegetation has been carefully studied in Braun-Blanquet method. The relationship between environmental factors including topography and some of the most current physicochemical features of soil and plant associations was researched by means of multiple discriminant analysis. Based on AFC and CAH methods, 8 associations and 1 sub-association were achieved including: Trifolio stellati-Quercetum brantii, Pistacio atlanticae-Quercetum brantii, Violo modestue-Quercetum brantii, Trifolio campestri-Quercetum brantii, Quercetum brantii, Thalictro sultanabadensi-Quercetum libani, Quercetum libani-acerotosum cinerascens, Quercos boissieri-Quercetum libani and Quercetum libani. These plant associations belong to Quercetea persicae class and Quercetalia persicae order. The effective environmental factors in division of plant associations based on multiple discriminant analysis include respectively: pH, landform index, Terrain shape index and aspect.
The Image of Bangkok as a Fashion City
Kanlaya Vanichbuncha
International Business and Management , 2012, DOI: 10.3968/j.ibm.1923842820120402.1060
Abstract: There are two main purposes of this study. The first purpose was to investigate the perception of and exposure to the project “Bangkok: The Fashion City”, study the image of the project “Bangkok: The Fashion City” by comparing it to the image of Tokyo, Hong Kong, and Singapore as a fashion hub. And the second purpose was to segment consumers on the basis of their opinions toward Bangkok as Asia’s fashion hub in an effort to understand the characteristics of consumers in Thailand and abroad and study the characteristics of consumers in Thailand and abroad by considering their opinions toward establishing Bangkok to be Asia’s fashion hub. The participants were selected from those living in 7 capital cities in the following countries: Thailand, Japan, Malaysia, Indonesia, Hong Kong, China and Singapore. The sampling technique employed was quota sampling by sex and age. To make comparisons between the images perceived by people from Thailand, Japan, Singapore and Hong Kong, a paired t-test and a correspondence analysis were used. In addition, nonhierarchical cluster analysis was conducted to classify the consumer opinions toward Thailand’s fashion industry. Regression analysis and discriminant analysis were used to find factors affecting consumer views on Thailand’s fashion industry. For the findings, we found out that foreigners were not informed of the happenings in the country’s fashion business. Most of the respondents were exposed to this subject via television while those from Malaysia and Singapore obtained the information via magazines and newspapers. Most respondents agreed that Japan was best suited to serve as a fashion hub in the region, with Hong Kong and Singapore ranked second and third, respectively. Thailand was ranked fourth in this regard. It was found that not only Thais but also Malaysians suggested Thailand be the regional fashion hub. Most consumers agreed to the fact that Japan gained prominence in all aspects of the industry, particularly the quality of the products, compared to Thailand, Hong Kong, Singapore and China. They also found Thailand was prominent in the product’s uniqueness and low prices. According to the findings, consumers could be divided into 3 groups on the basis of their opinions toward Thailand’s fashion industry. The first group, mostly consisting of respondents from Hong Kong and China, did not agree Thailand should be an ideal fashion hub in Asia. The second group, mostly consisting of respondents from Thailand, Malaysia and Indonesia, believed Thailand was suited to assume this role in this region. The third
Efficient Global Programming Model for Discriminant Analysis
International Journal on Computer Science and Engineering , 2011,
Abstract: Conventional statistical analysis includes the capacity to systematically assign individuals to groups. We suggest alternative assignment procedures, utilizing a set of interrelated goal programming formulations. This paper represents an effort to suggest ways by which the discriminant problem might reasonably be addressed via straightforward linear goal programming formulations. Simple and direct, such formulations may ultimately compete with conventional approaches - free of the classical assumptions and possessing a stronger intuitive appeal. We further demonstrate via simple illustration the potential of these procedures to play a significant part in addressing the discriminant problem, and indicate fundamental ideas that lay the foundation for other more sophisticated approaches.
Common environmental descriptors of two benthic amphi-atlantic mollusc assemblages
Absal?o, Ricardo S.;Moreira, J.;Troncoso, Jesus S.;
Brazilian Journal of Oceanography , 2006, DOI: 10.1590/S1679-87592006000100006
Abstract: two benthic mollusc assemblages of the continental shelf on both sides of the atlantic ocean, a tropical one in rio de janeiro, brazil, and another, temperate, in galicia, spain were investigated, with a view to finding common environmental descriptors which would explain, on a macro-scale, why these assemblages are there. both of the assemblages concerned show approximately the same species richness, about 150 taxa each. the molluscan fauna of both regions live on sandy sediments. the galician assemblages are at about 2-12 m depth, while those in rio de janeiro are at about 10-40 m depth. malacological assemblages were defined through cluster analysis and multiple discriminant analysis of the environmental data showed that each assemblage has its own environmental space. these assemblages have no species in common, but show the same phenological characters associated with each sedimentological facies. the same set of environmental variables (median sediment grain size, skewness, kurtosis, sorting, fine and medium sand fractions and depth) were selected as controlling these assemblages, suggesting that they play their role as general environmental descriptors.
The portuguese Vitis vinifera L. germplasm: genetic relations between wild and cultivated vines
Cunha,Jorge; Teixeira-Santos,Margarida; Veloso,Manuela; Carneiro,Luís; Eiras-Dias,José; Fevereiro,Pedro;
Ciência e Técnica Vitivinícola , 2010,
Abstract: portuguese wild vine populations are in an apparent geographic fringe of the species distribution. despite, portugal offers a unique richness in autochthonous cultivated varieties that contributes to the overall diversity of worldwide grapevine. in the different portuguese agro-ecosystems, grapevine plays an important role either as a border culture or an extensive crop. during the last years wild vine populations have been identified but only in southern riverside ecosystems. to conclude if the local wild vine germplasm is involved in the origin of cultivated grapevine we used the oiv recommend six nuclear and four chloroplastidial microsatellite loci to genotype and to established phylogenetic relationships between wild plants and cultivated grapevines. both native sylvestris and vinifera subspecies have a high genetic diversity and a sizeable number of rare alleles. portuguese wild vine populations showed a high level of intra-population diversity with most of the genetic diversity conserved within each population. wild vines seem to form a continuum and there is no clear population division. despite, a low, but still significant, genetic differentiation can be detected among the analyzed populations. there seem to be a close genetic relation between the wild plants and cultivated varieties. both subspecies mostly share the a and b chlorotypes, tipical of the iberian germplasms. in some cases we found a close genetic relation between cultivated varieties and wild plants. finally, some native grapevine cultivars have a higher genetic diversity that reveals introgression of foreign gene pool. this study contributes to establish the range of existing genetic variability in the portuguese native grapevine and wild vines germplasm. it also provides a baseline for future monitoring of the genetic diversity of the species in portugal and contributes with data to construct a core collection to preserve the existing variability and delineate conservation strategies for th
Geostatistical Studies and Anomalous Elements Detection, Bardaskan Area, Iran  [PDF]
Sina Alahgholi, Adel Shirazy, Aref Shirazi
Open Journal of Geology (OJG) , 2018, DOI: 10.4236/ojg.2018.87041
Abstract: The aim of this study is geostatistical analysis and detection of anomalous elements in the Bardaskan area (in geological map of Bardaskan on scale 1:100,000 which is provided by the GSI organization). The study area is located in Khorasan province of Iran. Due to the availability of lithogeochemical regular data in the region as well as the importance of exploration of metal minerals in order to simplify and summarize the geochemical map, geostatistical methods were used to identify the mineralization potential of the region. Initially, using single-variable and multivariate statistical methods, anomalous elements were separated. Then, the thresholds (various communities) for the titanium element that was most likely to be anomalous were identified. Using these limits, the discriminant analysis was applied to the elements. Titanium, iron and magnesium elements were identified as the main mineral elements in the region. These elements indicate mineralization in the mafic bed rocks. Finally the map of the concentration of titanium element was mapped across the region with Kriging interpolation method. As a result, two anomalies of the titanium element in the region were identified.
Optimal feature extraction and face recognition based on kernel machine-based one-parameter multiple discriminant analysis

WANG Shi-tong,

计算机应用 , 2006,
Abstract: A new algorithm, namely kernel machine-based one-parameter multiple discriminant analysis (K1PMDA), to extract optimal discriminant features was proposed and applied to face recognition. There are two problems in linear face recognition: One is that the distribution of face images with different pose, illumination and face expression is complex and nonlinear. The other is the small sample size (S3) problem. This problem occurs when the number of training samples is smaller than the dimensionality of feature vectors, which results in a singular within-class scatter matrix. For the former, kernel technique can be used to extract nonlinear feature, and for the latter, a disturbed parameter was introduced to overcome S3 problem. Three databases, namely ORL, Yale Group B, and UMIST were selected for evaluation. The results are encouraging.
Analyzing the Score Data of Five Wine Samples from Two Groups of Experts Based on R Software

明鹤, 张应应
Statistics and Applications (SA) , 2014, DOI: 10.12677/SA.2014.34018
By using R software, we discuss the evaluations of five wine samples by two groups of specialists and the rationality of the evaluations. First of all, by using the hypothesis testing of two normal population means, we judge whether there are significant score differences between two groups of specialists. The test results show consistency of scores of two groups of specialists, and thus the evaluation result has certain fairness and rationality. Secondly, by using multiple t test of the mean, we can investigate the degree of differentiation of different samples by the specialists. Under the significance level of 0.05, the specialists can separate sample 1 from samples 2, 3, and 5, samples 2 and 4, samples 3 and 4. By ordering the levels of five samples from high to low, we find that the specialists can basically distinguish samples with levels with level difference by 1. But specialists do not effectively distinguish samples 1 and 4 (level difference 1.5), samples 3 and 5 (level difference 1). Then we use the hierarchical clustering method to classify five samples to three classes: excellent, good, and bad. Finally, by using the distance discriminant analysis method, the discriminant function is established based on the training sample, then by discrimination of the training sample, we get specialists’ misjudgment rate and accurate rate, and thus we can use the discriminant function to classify the new samples.
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