PRINCIPAL COMPONENTS ANALYSIS OF DATA FROM SAXICOLOUS BRYOPHYTE VEGETATION AT STEPS BRIDGE, DEVON: I A QUANTITATIVE ASSESSMENT OF VARIATION IN THE VEGETATION

1967 ◽  
Vol 45 (1) ◽  
pp. 93-115 ◽  
Author(s):  
G. A. Yarranton
Keyword(s):  
Quantitative Analysis ◽  
Data Processing ◽  
Principal Components Analysis ◽  
Principal Components ◽  
Quantitative Assessment ◽  
Statistical Treatment ◽  
The Other ◽  
Dispersion Matrix ◽  
Components Analysis ◽  
Analysis Of Variation

The aim of the series of three papers, of which this is the first, is to produce a rigorous quantitative analysis of variation in vegetation and to correlate the results of the analysis with environmental variation. A general account is given of the Steps Bridge area and of the vegetation studied. The collection of samples of contact between species in the saxicolous bryophyte vegetation is described. To compare the effects of different methods of data processing, four matrices were calculated: a correlation and a dispersion matrix based on the joint and total occurrences of pairs of species in the samples, and a correlation and a covariance matrix based on the occurrences of pairs of species with all the other species in the samples. Results of principal components analyses of the four matrices are presented and compared and the appropriate circumstances for the use of each type of matrix are indicated. The components analyses are analyses of the distributional relationships of the species and are based on rigorous statistical treatment throughout.

Evaluation on Restoration of Ecological City of Ha’erbin

2010 ◽  
Vol 113-116 ◽  
pp. 938-942
Author(s):  
Mu Hua Cui
Keyword(s):  
Quantitative Analysis ◽  
Qualitative Analysis ◽  
Principal Components Analysis ◽  
Principal Components ◽  
Index System ◽  
Analysis Method ◽  
Components Analysis ◽  
Made In

This article is designed to carry out design of index system for evaluation of ecological city which is applicable to features of city of Ha’erbin on basis of actual conditions of Ha’erbin in principle of combination of qualitative analysis and quantitative analysis and to conduct evaluation on effect of restoration of ecological city of Ha’erbin with principal components analysis method. Results of evaluation show that some accomplishment has been made in terms of construction of ecological city of Ha’erbin and sub-system of environment, economy and society of Ha’erbin has been greatly improved since 2002.

scholarly journals A Novel Sky-Subtraction Method Based on Non-negative Matrix Factorisation with Sparsity for Multi-object Fibre Spectroscopy

2016 ◽  
Vol 33 ◽  
Author(s):  
Bo Zhang ◽  
Long Zhang ◽  
Zhongfu Ye
Keyword(s):  
Principal Components Analysis ◽  
Principal Components ◽  
Curve Fitting ◽  
The Other ◽  
Subtraction Method ◽  
B Spline ◽  
Spline Curve ◽  
Components Analysis ◽  
Matrix Factorisation

AbstractA novel sky-subtraction method based on non-negative matrix factorisation with sparsity is proposed in this paper. The proposed non-negative matrix factorisation with sparsity method is redesigned for sky-subtraction considering the characteristics of the skylights. It has two constraint terms, one for sparsity and the other for homogeneity. Different from the standard sky-subtraction techniques, such as the B-spline curve fitting methods and the Principal Components Analysis approaches, sky-subtraction based on non-negative matrix factorisation with sparsity method has higher accuracy and flexibility. The non-negative matrix factorisation with sparsity method has research value for the sky-subtraction on multi-object fibre spectroscopic telescope surveys. To demonstrate the effectiveness and superiority of the proposed algorithm, experiments are performed on Large Sky Area Multi-Object Fiber Spectroscopic Telescope data, as the mechanisms of the multi-object fibre spectroscopic telescopes are similar.

scholarly journals Diagnostic Petiole Anatomical Characters and their Systematc Importance in eighteen (18) species of the genus Tephrosia PERS (fabaceae) found in Nigeria

2019 ◽  
Vol 6 (1) ◽  
Author(s):  
Omoteso Oluwa ◽  
Dele Olowokudejo ◽  
Oluwatoyin Ogundipe
Keyword(s):  
Cluster Analysis ◽  
Principal Components Analysis ◽  
Principal Components ◽  
Statistical Treatment ◽  
Systematic Investigation ◽  
Data Matrix ◽  
Anatomical Characters ◽  
Components Analysis ◽  
And Cluster Analysis

A comprehensive systematic investigation on diagnostic petiole characters of eighteen species of Tephrosia, from family Fabaceae, tribe Milleteae. It habits the fringes often forests, and abandoned, and wastelands. A total of nine diagnostic polymorphic characters were observed, photographed, assessed,scoredand coded as Data matrix for quantitative statistical treatment. The 9 characters codes include PSY, POL, PVS, PPT, and PTE. others include PTA, PTO, PTC, and PTB. Principal Components Analysis (PC) and Cluster Analysis were carried out. Four PC were identified and Cluster analysis indicates twelve hierarchies.

scholarly journals Principal Components Analysis Utility in the Livestock Field

2016 ◽  
Vol 73 (2) ◽  
pp. 251
Author(s):  
Ancuta Simona Rotaru ◽  
Ioana Pop ◽  
Anamaria Vatca ◽  
Luisa Andronie
Keyword(s):  
Factor Analysis ◽  
Principal Components Analysis ◽  
Principal Components ◽  
Latent Variables ◽  
Principal Component ◽  
The Other ◽  
Data Sets ◽  
Method Factor ◽  
Two Factors ◽  
Components Analysis

Principal Component Analysis is a method factor - factor analysis - and is used to reduce data complexity by replacingmassive data sets by smaller sets. It is also used to highlight the way in which the variables are correlated with eachother and to determining the (less)latent variableswhich are behind the (more)measured variables. These latent variables are called factors, hence the name of the methodi.e. factor analysis. Our paper shows the applicability of Principal Components Analysis (PCA) in livestock area of study by carrying out a researchon some physiological characteristics in the case of tencow breeds.By using PCA only two factors have been preserved, concentrating over 80% of their information from the four variables in question, one factor concentrating weight and height and the other factor concentrating trunk circumference and weight at calving, respectively.

How distinct is ‘distinct quality’ of mood?

1997 ◽  
Vol 27 (2) ◽  
pp. 445-453 ◽  
Author(s):  
G. PARKER ◽  
J. ROUSSOS ◽  
K. EYERS ◽  
K. WILHELM ◽  
P. MITCHELL ◽  
...  
Keyword(s):  
Principal Components Analysis ◽  
Principal Components ◽  
Mood State ◽  
Quality Criterion ◽  
The Other ◽  
Clinical Feature ◽  
Melancholic Depression ◽  
Dsm Iv ◽  
Components Analysis

Background. The DSM-IV criteria for melancholia include the clinical feature ‘distinct quality’, defined as a mood state differing from that experienced in bereavement. Both propositions – its specificity to melancholia and its definition – remain problematical.Methods. We examine both propositions by analysing an adjective checklist completed by melancholic and non-melancholic depressed subjects, as well as by a bereaved sample. The checklist was refined by a principal components analysis to four scales – one assessing a general ‘mood’ severity or dysphoric dimension, and the other three assessing dimensions of ‘fatigue’, ‘numbness’ and ‘guilt’.Results. If the concept of ‘distinct quality’ has validity, we would require specificity of the refined qualitative constructs to melancholic depression. The ‘numbness’ component met that requirement, but only to a degree. While bereaved subjects did differ from those with melancholic depression on a number of our refined qualitative mood domains, such differences appeared more related to lower levels of depression in the bereaved sample.Conclusions. We argue for deleting the ‘distinct quality’ criterion from diagnostic checklists of melancholia until its definition has been improved, its utility demonstrated and its specificity to any depressive subtype established as having clinical significance.

Sub-syndromes of tardive dyskinesia

1980 ◽  
Vol 10 (3) ◽  
pp. 513-520 ◽  
Author(s):  
T. Kidger ◽  
T. R. E. Barnes ◽  
T. Trauer ◽  
P. J. Taylor
Keyword(s):  
Tardive Dyskinesia ◽  
Head And Neck ◽  
Principal Components Analysis ◽  
Principal Components ◽  
Reliable Method ◽  
The Other ◽  
Parkinsonian Syndrome ◽  
Limb Movements ◽  
Components Analysis

SYNOPSISA reliable method for recording the site and duration of purposeless movements was devised. With this method 267 subjects were studied, 182 of whom had been exposed to neuroleptics. The results were submitted to a principal components analysis and 3 movement dimensions emerged. One group of movements resembled a parkinsonian syndrome. The other 2 groups of movements both conformed to the generally accepted criteria for tardive dyskinesia. These groups were: (1) head and neck movements and (2) trunk and limb movements. The possibility of the second and third groups representing clinically relevant sub-syndromes of tardive dyskinesia is discussed.

Soil surface lichens in arid and subarid south-eastern Australia. II. Phytosociology and geographic zonation

1972 ◽  
Vol 20 (2) ◽  
pp. 215 ◽  
Author(s):  
RW Rogers
Keyword(s):  
Principal Components Analysis ◽  
Principal Components ◽  
Group Identification ◽  
Soil Surface ◽  
The Other ◽  
Influence Analysis ◽  
South Eastern ◽  
Eastern Australia ◽  
Species Groups ◽  
Components Analysis

Five lichen species groups were delimited, principal components analysis and influence analysis being used as aids to group identification. With these same techniques it was demonstrated that two of the species groups formed "background" floras in adjacent geographic areas, the other three species groups, being superimposed upon the "background" floras to produce five separate geographic zones of lichen distribution.

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