Discriminant function analysis of atlas and axis vertebrae of the toothed whale to facilitate species identification in zooarchaeological specimens

2020 ◽  
Vol 30 (6) ◽  
pp. 843-854
Author(s):  
Cholawit Thongcharoenchaikit ◽  
Masaki Eda
Keyword(s):  
Species Identification ◽  
Discriminant Function ◽  
Discriminant Function Analysis ◽  
Function Analysis ◽  
Toothed Whale ◽  
Atlas And Axis

Differences Among Species in Compact Bone Tissue Microstructure of Mammalian Skeleton: Use of a Discriminant Function Analysis for Species Identification

2006 ◽  
Vol 51 (6) ◽  
pp. 1235-1239 ◽  
Author(s):  
Monika Martiniaková ◽  
Birgit Grosskopf ◽  
Radoslav Omelka ◽  
Mária Vondráková ◽  
Mária Bauerová
Keyword(s):  
Bone Tissue ◽  
Species Identification ◽  
Discriminant Function ◽  
Discriminant Function Analysis ◽  
Function Analysis ◽  
Compact Bone ◽  
Tissue Microstructure ◽  
Compact Bone Tissue

Diagnoses Generated by Numerical Taxonomic Methods Applied to Standard Blood Variables

1980 ◽  
Vol 19 (04) ◽  
pp. 205-209
Author(s):  
L. A. Abbott ◽  
J. B. Mitton
Keyword(s):  
Liver Cirrhosis ◽  
Renal Disease ◽  
Principal Components Analysis ◽  
Discriminant Function ◽  
Principal Components ◽  
Discriminant Function Analysis ◽  
Chronic Renal Disease ◽  
Function Analysis ◽  
Infectious Hepatitis ◽  
Components Analysis

Data taken from the blood of 262 patients diagnosed for malabsorption, elective cholecystectomy, acute cholecystitis, infectious hepatitis, liver cirrhosis, or chronic renal disease were analyzed with three numerical taxonomy (NT) methods : cluster analysis, principal components analysis, and discriminant function analysis. Principal components analysis revealed discrete clusters of patients suffering from chronic renal disease, liver cirrhosis, and infectious hepatitis, which could be displayed by NT clustering as well as by plotting, but other disease groups were poorly defined. Sharper resolution of the same disease groups was attained by discriminant function analysis.

scholarly journals Description of Echolocation Call Parameters for Urban Bats in Vietnam as a Step Towards a More Integrated Acoustic Monitoring of Urban Wildlife in Southeast Asia

Diversity ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 18
Author(s):  
Long Kim Pham ◽  
Bang Van Tran ◽  
Quy Tan Le ◽  
Trung Thanh Nguyen ◽  
Christian C. Voigt
Keyword(s):  
Discriminant Function ◽  
Discriminant Function Analysis ◽  
Function Analysis ◽  
Quantitative Description ◽  
Southeast Asian ◽  
Asian Countries ◽  
Echolocation Call ◽  
Echolocation Calls ◽  
Pilot Work ◽  
Southeast Asian Countries

This study is the first step towards more systematic monitoring of urban bat fauna in Vietnam and other Southeast Asian countries by collecting bat echolocation call parameters in Ho Chi Minh and Tra Vinh cities. We captured urban bats and then recorded echolocation calls after releasing in a tent. Additional bat’s echolocation calls from the free-flying bats were recorded at the site where we captured bat. We used the obtained echolocation call parameters for a discriminant function analysis to test the accuracy of classifying these species based on their echolocation call parameters. Data from this pilot work revealed a low level of diversity for the studied bat assemblages. Additionally, the discriminant function analysis successfully classified bats to four bat species with an accuracy of >87.4%. On average, species assignments were correct for all calls from Taphozous melanopogon (100% success rate), for 70% of calls from Pipistrellus javanicus, for 80.8% of calls from Myotis hasseltii and 67.3% of calls from Scotophilus kuhlii. Our study comprises the first quantitative description of echolocation call parameters for urban bats of Vietnam. The success in classifying urban bats based on their echolocation call parameters provides a promising baseline for monitoring the effect of urbanization on bat assemblages in Vietnam and potentially also other Southeast Asian countries.

Predictors of hyoid fracture in hanging: Discriminant function analysis of morphometric variables

2010 ◽  
Vol 12 (3) ◽  
pp. 113-116 ◽  
Author(s):  
Partha Pratim Mukhopadhyay
Keyword(s):  
Discriminant Function ◽  
Discriminant Function Analysis ◽  
Function Analysis

Mineralogy of Egyptian Bentonitic Clays I: Discriminant Function Analysis

2012 ◽  
Vol 60 (4) ◽  
pp. 387-404 ◽  
Author(s):  
Mohamed Agha ◽  
Ray E. Ferrell ◽  
George F. Hart
Keyword(s):  
Discriminant Function ◽  
Discriminant Function Analysis ◽  
Function Analysis

Using discriminant function analysis to identify Holocene tephras based on magnetite composition: a case study from the Sunwapta Pass area, Jasper National Park

1986 ◽  
Vol 23 (6) ◽  
pp. 804-812 ◽  
Author(s):  
A. B. Beaudoin ◽  
R. H. King
Keyword(s):  
National Parks ◽  
Discriminant Function ◽  
Discriminant Function Analysis ◽  
National Park ◽  
Function Analysis ◽  
Classification Schemes ◽  
Jasper National Park ◽  
Multivariate Method ◽  
Reference Samples

The magnetite composition from three sets of samples of Mazama, St. Helens set Y, and Bridge River tephras from Jasper and Banff national parks are used to test whether discriminant function analysis can unambiguously distinguish these tephras. The multivariate method is found to be very sensitive to the change in reference samples. St. Helens set Y tephra is clearly distinguished. However, discrimination between Mazama and Bridge River tephras is less distinct. A set of unknown tephras from the Sunwapta Pass area was used to test the classification schemes. Unknown tephras are assigned to different tephra types depending on which reference tephra set is used in the discriminant function analysis.

Measurement of Informal Selection Processes

1967 ◽  
Vol 25 (2) ◽  
pp. 421-436
Author(s):  
Rayman W. Bortner
Keyword(s):  
Discriminant Function ◽  
Discriminant Function Analysis ◽  
Function Analysis ◽  
Community Sample ◽  
Reference Points ◽  
Self Concept ◽  
Selection Processes ◽  
Step Down ◽  
Eligibility Requirements ◽  
Additional Reference

When statements of formal eligibility requirements fail to account for the characteristics of institutional populations, there is a tendency to resort to speculative explanations. This study examined some methods for empirical evaluations of these speculative notions. Univariate and step-down analyses did not aid in conceptualizing informal selection processes in this study; a discriminant function analysis seemed to provide an adequate approach to a synthesis. The method was illustrated by examining definable subsamples in a VA domiciliary which were compared with a non-institutional, community sample; means of the standardization samples for the tests used provided additional reference points for comparison. For these particular subsamples from this institution, alterations in self concept appeared to provide the single unifying theme which best integrated the diverse differences among the groups.

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