scholarly journals Applying Multivariate Statistical Methods for Predicting Pinus Forest Fire Danger at Bidoup-Nui Ba National Park

2021 ◽  
pp. 45-53
Author(s):  
Ле Ван Хыонг ◽  
Нгуен Нгок Киенг ◽  
Нгуен Данг Хой ◽  
Данг Хунг Куонг
Keyword(s):  
Statistical Methods ◽  
Forest Fire ◽  
Canonical Correlation ◽  
National Park ◽  
Function Analysis ◽  
Fire Danger ◽  
Multivariate Statistical Methods ◽  
Multivariate Statistical ◽  
Forest Fire Danger ◽  
Classification Function

The paper presents results of applying multivariate statistical methods (CCA: canonical correlation analysis and DFA: discriminant function analysis) for determining canonical correlation between a set of variables {T, H, m1, K} and a set of variables {Pc, Tc} (T: temperature, H: relative humidity, m1: mass of dry fuels, K: burning coefficient, K = m1/M, with M: total mass of fire fuels, Pc: % burned fuels and Tc: burningtime) as well as through results of discriminant function analysis DFA to set up models of predicting forest fire danger at Bidoup - Nui Ba National Park. From research data in November, December, January, February and March in the period of 2015-2017 from 340 sampling plots (each 2mx2m), at Bidoup - Nui Ba National Park, we carry on data processing on Excel (calculating) and Statgraphics (multivariate statistical methods: CCA&DFA). Three results were revealed from our analysis: (i) Canonical correlation between a set of variables {T, H, m1, K} and a set of variables {Pc, Tc} is highly significant (R = 0.675581 & P = 3.17*10-58<< 0.05); therefore, we can use a set of variables {T, H, m1, K} in models of predicting forest fire danger, (ii) Coefficients of standardized & unstandardized canonical discriminant functions (SCDF &UCDF) and Fisher classification function (FCF) are determined, (iii) Setting up two models of predicting forest fire danger (Mahalanobis distance model & Fisher classification function model).

Classification of rural households due to directions and types of outgoings

2017 ◽  
Vol 62 (8) ◽  
pp. 53-73
Author(s):  
Marlena Piekut
Keyword(s):  
Statistical Methods ◽  
Discriminant Function ◽  
Discriminant Function Analysis ◽  
Function Analysis ◽  
Rural Households ◽  
Analysis Data ◽  
Multivariate Statistical Methods ◽  
Multivariate Statistical ◽  
Per Capita

The aim of the study is to isolate groups of rural households with similar outgoings and to describe them by socio-demographic and economic characteristics. It was carried out using multivariate statistical methods such as k-means cluster and discriminant function analysis. Data from the CSO survey of household budgets for the years 2004 and 2012 were used for the research purpose. The research resulted in the division of rural households into four groups considering the outgoings, where one group covered more than 2/3 of the households. Variables which discriminated the membership of rural households to certain groups to the largest extent were the number of people in the household and disposable income per capita.

The Limitations of Multivariate Statistical Methods in the Mensuration of Human Misery

1989 ◽  
Vol 23 (4) ◽  
pp. 503-511 ◽  
Author(s):  
Wayne Hall
Keyword(s):  
Statistical Methods ◽  
Function Analysis ◽  
Depressive Illness ◽  
Psychiatric Research ◽  
Multivariate Methods ◽  
Multivariate Statistical Methods ◽  
Multivariate Statistical ◽  
High Expectations ◽  
Do So

Multivariate statistical methods have been widely used in the analysis of the multiple symptom data which are routinely collected in psychiatric research on the classification of depressive illnesses. The most commonly used methods, those of factor analysis and discriminant function analysis, were introduced into research on the classification of depressive illness with unreasonably high expectations about what they could achieve. The failure to realize these expectations has produced scepticism in some quarters about the usefulness of multivariate methods in psychiatric research. When evaluated more circumspectly, multivariate statistical methods have made a contribution to our understanding of depressive illnesses, and they will continue to do so, if they are used with more reasonable expectations.

Null se constructions in Brazilian and European Portuguese: morphosyntactic deletion or emergence of new constructions?

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Augusto Soares da Silva ◽  
Susana Afonso ◽  
Dafne Palú ◽  
Karlien Franco
Keyword(s):  
Statistical Methods ◽  
External Factors ◽  
Important Predictor ◽  
Cognitive Grammar ◽  
Multivariate Statistical Methods ◽  
Multivariate Statistical ◽  
Passive Construction ◽  
European Portuguese ◽  
Change Of State ◽  
The Moment

Abstract Se constructions designate a set of polysemous constructions along a transitivity continuum marked by the clitic se that perform various functions: reflexive/reciprocal, middle, anticausative, passive, and impersonal. A counterpart of these constructions without the clitic – the null se construction – is also attested. Based on an extensive usage-feature and profile-based analysis, and using multivariate statistical methods, we analyze, considering Cognitive Grammar, the conceptual, structural, and lectal factors that determine the choice between overt and null se constructions. The results of the study show that the null constructions are far more frequent in Brazilian (BP) than in European Portuguese (EP). In BP, the focus on the moment of change is a crucial factor for the overt/null variation in reflexive/reciprocal, middle, anticausative, and impersonal constructions. If the moment of the change of state is profiled, the overt se construction is usually produced. If the moment of change is not profiled, the null se construction is preferred. External factors also play a role in the variation. Register is an important predictor for the observed variation of the anticausative construction, and the only predictor for the overt/null variation in the case of the passive construction. In EP, the null se variant is mainly limited to anticausative constructions. In all cases of null constructions, there is a shift to an absolute construal, which has an impact on the way that the transitivity continuum is conceptualized.

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