scholarly journals Directly modelling population dynamics in the South American Arid Diagonal using 14 C dates

2020 ◽  
Vol 376 (1816) ◽  
pp. 20190723 ◽  
Author(s):  
Adrian Timpson ◽  
Ramiro Barberena ◽  
Mark G. Thomas ◽  
César Méndez ◽  
Katie Manning
Keyword(s):  
Population Dynamics ◽  
Goodness Of Fit ◽  
Population Change ◽  
Piecewise Linear ◽  
South American ◽  
Initial Growth ◽  
Sample Sizes ◽  
The South ◽  
Goodness Of Fit Test ◽  
True Population

Large anthropogenic 14 C datasets are widely used to generate summed probability distributions (SPDs) as a proxy for past human population levels. However, SPDs are a poor proxy when datasets are small, bearing little relationship to true population dynamics. Instead, more robust inferences can be achieved by directly modelling the population and assessing the model likelihood given the data. We introduce the R package ADMUR which uses a continuous piecewise linear (CPL) model of population change, calculates the model likelihood given a 14 C dataset, estimates credible intervals using Markov chain Monte Carlo, applies a goodness-of-fit test, and uses the Schwarz Criterion to compare CPL models. We demonstrate the efficacy of this method using toy data, showing that spurious dynamics are avoided when sample sizes are small, and true population dynamics are recovered as sample sizes increase. Finally, we use an improved 14 C dataset for the South American Arid Diagonal to compare CPL modelling to current simulation methods, and identify three Holocene phases when population trajectory estimates changed from rapid initial growth of 4.15% per generation to a decline of 0.05% per generation between 10 821 and 7055 yr BP, then gently grew at 0.58% per generation until 2500 yr BP. This article is part of the theme issue ‘Cross-disciplinary approaches to prehistoric demography’.

On the use of chi-square analyses in studies of resource utilization

1991 ◽  
Vol 21 (1) ◽  
pp. 58-65 ◽  
Author(s):  
Dennis E. Jelinski
Keyword(s):  
Resource Utilization ◽  
Goodness Of Fit ◽  
Small Sample ◽  
Homogeneity Test ◽  
Type I ◽  
Sample Sizes ◽  
Goodness Of Fit Test ◽  
Chi Square ◽  
Test Of Homogeneity ◽  
Small Sample Sizes

Chi-square (χ2) tests are analytic procedures that are often used to test the hypothesis that animals use a particular food item or habitat in proportion to its availability. Unfortunately, several sources of error are common to the use of χ2 analysis in studies of resource utilization. Both the goodness-of-fit and homogeneity tests have been incorrectly used interchangeably when resource availabilities are estimated or known apriori. An empirical comparison of the two methods demonstrates that the χ2 test of homogeneity may generate results contrary to the χ2 goodness-of-fit test. Failure to recognize the conservative nature of the χ2 homogeneity test, when "expected" values are known apriori, may lead to erroneous conclusions owing to the increased possibility of committing a type II error. Conversely, proper use of the goodness-of-fit method is predicated on the availability of accurate maps of resource abundance, or on estimates of resource availability based on very large sample sizes. Where resource availabilities have been estimated from small sample sizes, the use of the χ2 goodness-of-fit test may lead to type I errors beyond the nominal level of α. Both tests require adherence to specific critical assumptions that often have been violated, and accordingly, these assumptions are reviewed here. Alternatives to the Pearson χ2 statistic are also discussed.

scholarly journals Goodness of Fit Test of an Autocorrelated Time Series Cubic Smoothing Spline Model

2021 ◽  
pp. 191-200
Author(s):  
Samuel Olorunfemi Adams ◽  
Davies Abiodun Obaromi ◽  
Alumbugu Auta Irinews
Keyword(s):  
Time Series ◽  
Goodness Of Fit ◽  
Cross Validation ◽  
Real Life ◽  
Smoothing Spline ◽  
Selection Methods ◽  
Sample Sizes ◽  
Goodness Of Fit Test ◽  
Generalized Cross Validation ◽  
Non Parametric

We investigated the finite properties as well as the goodness of fit test for the cubic smoothing spline selection methods like the Generalized Maximum Likelihood (GML), Generalized Cross-Validation (GCV) and Mallow CP criterion (MCP) estimators for time-series observation when there is the presence of Autocorrelation in the error term of the model. The Monte-Carlo study considered 1,000 replication with six sample sizes: 30; 60; 120; 240; 480 and 960, four degree of autocorrelations; 0.1; 0.3; 0.5; and 0.9 and three smoothing parameters; lambdaGML= 0.07271685, lambdaGCV= 0.005146929, lambdaMCP= 0.7095105. The cubic smoothing spline selection methods were also applied to a real-life dataset. The Predictive mean square error, R-square, and adjusted R-square criteria for assessing finite properties and goodness of fit among competing models discovered that the performance of the estimators is affected by changes in the sample sizes and autocorrelation levels of the simulated and real-life data set. The study concluded that the Generalized Cross-Validation estimator provides a better fit for Autocorrelated time series observation. It is recommended that the GCV works well at the four autocorrelation levels and provides the best fit for time-series observations at all sample sizes considered. This study can be applied to; non –parametric regression, non –parametric forecasting, spatial, survival and econometric observations.

Comparative biogeography and biology of the South American locust, Schistocerca cancellata(Serville), and the south african desert locust, s. gregaria flaviventris(Burmeister) (Orthoptera: Acrididae): a review

1986 ◽  
Vol 76 (1) ◽  
pp. 1-20 ◽  
Author(s):  
Z. Waloff ◽  
D. E. Pedgley
Keyword(s):  
Population Dynamics ◽  
South America ◽  
South African ◽  
Adult Stage ◽  
Reproductive Capacity ◽  
South American ◽  
Desert Locust ◽  
The South ◽  
Breeding Migration ◽  
And Migration

AbstractA comparison is made of the distribution, breeding, migration and population dynamics of Schistocerca cancellata (Serville) in South America and S. gregaria flaviventris (Burmeister) in southern Africa. The annual patterns of breeding and migration are strongly influenced by the weather and its seasonal variations. Breeding is confined to the summer rains, and outbreak regions lie in the driest parts of the distribution areas, where habitats are unstable but where high reproductive capacity allows the occasionally abundant rains to lead to plagues. The long dry season is passed in the mobile, downwind-displacing adult stage, survival being assisted by flexibility of rates of sexual maturation and of egg development. Some comparisons are made with S. gregaria gregaria (Forskål).

scholarly journals Problems of nonparametric goodness-of-fit test application in tasks of measurement results processing

2021 ◽  
pp. 47-66
Author(s):  
Boris Lemeshko ◽  
◽  
Stanislav Lemeshko ◽  
Keyword(s):  
Measurement Errors ◽  
Goodness Of Fit ◽  
Estimation Method ◽  
Asymptotic Distributions ◽  
Test Statistics ◽  
Sample Sizes ◽  
Asymptotic Results ◽  
Goodness Of Fit Test ◽  
Composite Hypotheses ◽  
Simple And Composite Hypotheses

It is argued that in most cases two reasons underlie the incorrect application of nonparametric goodness-of-fit tests in various applications. The first reason is that when testing composite hypotheses and evaluating the parameters of the law for the analyzed sample, classical results associated with testing simple hypotheses are used. When testing composite hypotheses, the distributions of goodness-of-fit statistics are influenced by the form of the observed law F(x, q) corresponding to the hypothesis being tested, by the type and number of estimated parameters, by the estimation method, and in some cases by the value of the shape parameter. The paper shows the influence of all mentiomed factors on the distribution of test statistics. It is emphasized that, when testing composite hypotheses, the neglect, of the fact that the test has lost the property of “freedom from distribution” leads to an increase in the probability of the 2nd kind errors. It is shown that the distribution of the statistics of the test necessary for the formation of a conclusion about the results of testing a composite hypothesis can be found using simulation in an interactive mode directly in the process of testing. The second reason is associated with the presence of round-off errors which can significantly change the distributions of test statistics. The paper shows that asymptotic results when testing simple and composite hypotheses can be used with round -off errors D much less than the standard deviation s of the distribution law of measurement errors and sample sizes n not exceeding some maximum values. For sample sizes larger than these maximum values, the real distributions of the test statistics deviate from asymptotic ones towards larger statistics values. In such situations, the use of asymptotic distributions to arrive at a conclusion about the test results leads to an increase in the probabilities of errors of the 1st kind (to the rejection of a valid hypothesis being tested). It is shown that when the round-off errors and s are commensurable, the distributions of the test statistics deviate from the asymptotic distributions for small n. And as n grows, the situation only gets worse. In the paper, changes in the distributions of statistics under the influence of rounding are demonstrated both when testing both simple and composite hypotheses. It is shown that the only way out that ensures the correctness of conclusions according to the applied tests in such non-standard conditions is the use of real distributions of statistics. This task can be solved interactively (in the process of verification) and rely on computer research technologies and the apparatus of mathematical statistics.

Postharvesting population dynamics of the South American sea lion (Otaria byronia) in the southwestern Atlantic

2014 ◽  
Vol 31 (3) ◽  
pp. 963-978 ◽  
Author(s):  
Valentina Franco-Trecu ◽  
Massimiliano Drago ◽  
Claudia Baladán ◽  
Mateo D. García-Olazábal ◽  
Enrique A. Crespo ◽  
...  
Keyword(s):  
Population Dynamics ◽  
South American ◽  
Southwestern Atlantic ◽  
The South ◽  
Sea Lion ◽  
South American Sea Lion

Cnidochloa: A New Genus of Grasses from Brazil (Poaceae: Panicoideae: Paniceae)

2020 ◽  
Vol 105 (2) ◽  
pp. 183-194
Author(s):  
Fernando O. Zuloaga ◽  
Sandra S. Aliscioni ◽  
M. Amalia Scataglini
Keyword(s):  
New Genus ◽  
Phylogenetic Position ◽  
South American ◽  
The South ◽  
South American Species ◽  
Molecular Characters

Generic boundaries of the South American species Panicum longipedicellatum Swallen are explored and compared with allied genera of the tribe Paniceae. On the basis of morphological, anatomical, and molecular characters a new genus, Cnidochloa Zuloaga, is proposed. The phylogenetic position of the new genus within the Paniceae is evaluated.

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