Comparison of multivariate analyses using taxonomic data of Oxalis

1976 ◽  
Vol 54 (14) ◽  
pp. 1637-1646 ◽  
Author(s):  
Melinda F. Denton ◽  
Roger del Moral
Keyword(s):  
Discriminant Analysis ◽  
Hierarchical Clustering ◽  
North American ◽  
Conventional Treatment ◽  
Multivariate Analyses ◽  
Stepwise Discriminant Analysis ◽  
Multivariate Techniques ◽  
Clustering Method ◽  
Phenetic Classification ◽  
Information Statistic

Several multivariate techniques are used to analyze the resemblances between the 25 North American taxa of Oxalis section Ionoxalis. Results from each of three clustering strategies are subjected to stepwise discriminant analysis for refinement and reallocation. The resultant phenetic classifications are compared with each other and with a recent conventional treatment using the same data. Affinities of the taxa, along with new relationships indicated by these analyses, are discussed. A polythetic hierarchical clustering method using an information statistic produces the most efficient and reliable phenetic classification and is recommended for use in systematic studies.

scholarly journals Surface Water Quality Assessment of Wular Lake, A Ramsar Site in Kashmir Himalaya, Using Discriminant Analysis and WQI

2014 ◽  
Vol 2014 ◽  
pp. 1-18 ◽  
Author(s):  
Salim Aijaz Bhat ◽  
Ashok K. Pandit
Keyword(s):  
Water Quality ◽  
Discriminant Analysis ◽  
Quality Data ◽  
Stepwise Discriminant Analysis ◽  
Multivariate Techniques ◽  
Kashmir Himalaya ◽  
Water Quality Data ◽  
Data Set ◽  
Total N ◽  
The Mean

Multivariate techniques, discriminant analysis, and WQI were applied to analyze a water quality data set including 27 parameters at 5 sites of the Lake Wular in Kashmir Himalaya from 2011 to 2013 to investigate spatiotemporal variations and identify potential pollution sources. Spatial and temporal variations in water quality parameters were evaluated through stepwise discriminant analysis (DA). The first spatial discriminant function (DF) accounted for 76.5% of the total spatial variance, and the second DF accounted for 19.1%. The mean values of water temperature, EC, total-N, K, and silicate showed a strong contribution to discriminate the five sampling sites. The mean concentration of NO2-N, total-N, and sulphate showed a strong contribution to discriminate the four sampling seasons and accounted for most of the expected seasonal variations. The order of major cations and anions was Ca2+>Mg2+> Na+>K+ and Cl->SO42->SiO22- respectively. The results of water quality index, employing thirteen core parameters vital for drinking water purposes, showed values of 49.2, 46.5, 47.3, 40.6, and 37.1 for sites I, II, III, IV, and V, respectively. These index values reflect that the water of lake is in good condition for different purposes but increased values alarm us about future repercussions.

scholarly journals Genetic divergence in pepper genotypes from southwest Goiás

2012 ◽  
Vol 36 (5) ◽  
pp. 498-506 ◽  
Author(s):  
Renata Cristina Alvares ◽  
Edésio Fialho dos Reis ◽  
Jefferson Fernando Naves Pinto
Keyword(s):  
Genetic Diversity ◽  
Hierarchical Clustering ◽  
Genetic Divergence ◽  
Block Design ◽  
Plant Genetic Resources ◽  
Germplasm Conservation ◽  
Multivariate Techniques ◽  
Clustering Method ◽  
Cophenetic Correlation ◽  
Breeding Programs

Knowledge on the genetic diversity in genebanks is important for germplasm conservation and use in breeding programs, where it can reduce time and costs of breeding of new genotypes. The purpose of this study was to evaluate the genetic divergence among 137 genotypes of Capsicum chinense Jacq. by morphological descriptors and multivariate techniques, with a view to the identification of groups for promising crosses for breeding programs. The experiment was conducted in a greenhouse, arranged in a randomized complete block design with four replications, where each plot consisted of a pot with one plant. The 20 descriptors recommended by the International Plant Genetic Resources Institute - IPGRI were considered for the morphological characterization. By analysis of variance, significant differences between genotypes were detected for the studied descriptors. Clustering by the Tocher optimization method formed five groups, and by the hierarchical clustering method UPGMA, 11 groups. Based on larger distances intergroup, crosses are recommended among genotypes of the groups II x V, II x IV, and I x V for the Tocher method, and by UPGMA among genotypes of the groups VI x XI, II x XI, IV x XI,. The cophenetic correlation coefficient for the hierarchical clustering method UPGMA was 0.797 (p <0.01). The traits that contributed most to the total genetic diversity were number of days to flowering and plant height.

scholarly journals A hierarchical clustering method for random intervals based on a similarity measure

2021 ◽  
Author(s):  
Ana Belén Ramos-Guajardo
Keyword(s):  
Hierarchical Clustering ◽  
Similarity Measure ◽  
Clustering Algorithm ◽  
Real Life ◽  
Stopping Criterion ◽  
Clustering Method ◽  
Bootstrap Test ◽  
Empirical Performance ◽  
Random Intervals ◽  
Expected Values

AbstractA new clustering method for random intervals that are measured in the same units over the same group of individuals is provided. It takes into account the similarity degree between the expected values of the random intervals that can be analyzed by means of a two-sample similarity bootstrap test. Thus, the expectations of each pair of random intervals are compared through that test and a p-value matrix is finally obtained. The suggested clustering algorithm considers such a matrix where each p-value can be seen at the same time as a kind of similarity between the random intervals. The algorithm is iterative and includes an objective stopping criterion that leads to statistically similar clusters that are different from each other. Some simulations to show the empirical performance of the proposal are developed and the approach is applied to two real-life situations.

scholarly journals Evaluation of crisphead lettuce cultivars in different cover types by manova and discriminant analysis

2013 ◽  
Vol 31 (3) ◽  
pp. 439-444
Author(s):  
Izabela Regina C de Oliveira ◽  
Marcelo T Rezende ◽  
Carlos Tadeu dos S Dias ◽  
Daniela de S Gomes ◽  
Élberis P Botrel ◽  
...  
Keyword(s):  
Discriminant Analysis ◽  
Cover Crops ◽  
Environmental Sustainability ◽  
Cover Crop ◽  
Univariate Analysis ◽  
Polyethylene Film ◽  
Standard Errors ◽  
Multivariate Techniques ◽  
Discriminant Analyses ◽  
Plot Design

In many agricultural experiments the variables are biologically correlated and it is inappropriate to study them only under univariate analysis. Therefore, we evaluated commercial characteristics of crisphead lettuce cultivars and covers under a multivariate approach, using canonical discriminant analysis. We used a split plot design and we tested the cover crop, cultivar and interaction effects by using MANOVA (α= 5%). Means and its standard errors were obtained for average total weight, weight of the head, volume and density of plants. Canonical discriminant analyses were performed using PROC CANDISC procedure in SAS (SAS Institute, 2008) system. Canonical plots were obtained using JMP 9.0 (SAS Institute, 2010) linked to SAS database. With these plots it was possible to note the differences among factors levels. When polyethylene film was used as cover the plants had inferior commercial characteristics than plants in which cover crops were used. Thus, the cover with polyethylene film can be discouraged in the cultivation of crisphead lettuce, promoting environmental sustainability. We suggest these multivariate techniques in horticulture studies.

scholarly journals Application of multivariate techniques in the evaluation of pure lines of beans

2016 ◽  
Vol 46 (9) ◽  
pp. 1535-1541 ◽  
Author(s):  
Rodolfo Schmit ◽  
Rita Carolina de Melo ◽  
Thayse Cristine Vieira Pereira ◽  
Mattheus Beck ◽  
Altamir Frederico Guidolin ◽  
...  
Keyword(s):  
Discriminant Analysis ◽  
Discriminant Function ◽  
Block Design ◽  
Original Data ◽  
Inbred Lines ◽  
Canonical Discriminant Analysis ◽  
Multivariate Techniques ◽  
Testing Hypotheses ◽  
Randomized Block Design ◽  
Pure Lines

ABSTRACT: The objective of this study was to apply multivariate techniques, canonical discriminant analysis, and multivariate contrasts, indicating the most favorable inferences in the evaluation of pure lines of beans. The study was conducted at the experimental field of the Institute for Breeding and Molecular Genetics, in Lages, SC, Brazil. The experiment was composed of 24 pure lines of beans from the Santa Catarina test of cultivars. Plant height, numbers of pods and grains per plant, and stem diameter were the variables measured. The complete randomized block design was used with four replications. The data were subjected to multivariate analysis of variance, canonical discriminant analysis, multivariate contrasts and univariate contrasts. The first canonical discriminant function has captured 81% of the total variation in the data. The Scott-Knott test showed two groups of inbred lines at the average -of scores of the first canonical discriminant function. It was considered that testing hypotheses with the canonical scores may result in loss of information obtained from the original data. Multivariate contrasts indicated differences within the group formed by the Scott-Knott test. The canonical discriminant analysis and multivariate contrasts are excellent techniques to be combined in the multivariate assessment, being used to explore and test hypotheses, respectively.

scholarly journals Statistical Analysis of Word Frequency Distribution in Lithuanian Texts of Different Genres

2016 ◽  
Vol 55 (1) ◽  
pp. 61-69
Author(s):  
Neringa Bružaitė ◽  
Tomas Rekašius
Keyword(s):  
Statistical Analysis ◽  
Word Frequency ◽  
Frequency Distribution ◽  
Hierarchical Clustering ◽  
Distance Measure ◽  
Structural Type ◽  
Clustering Method ◽  
Jaccard Distance ◽  
Word Frequencies ◽  
Word Frequency Distribution

The paper examines Lithuanian texts of different authors and genres. The main points ofinterest – the number of words, the number of different words and word frequencies. Structural type distributionand Zipf’s law are applied for describing the frequency distribution of words in the text. It is obvious that thelexical diversity of any text can be defined by different words that are used in the text, also called vocabulary.It is shown that the information contained in a reduced vocabulary is enough for dividing the texts analyzedin this article into groups by genre and author using a hierarchical clustering method. In this case, distancesbetween clusters are measured using the Jaccard distance measure, and clusters are aggregated using the Wardmethod.

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