Computational Mathematics and Applied Statistics
Rapid advances in modelling research have created new challenges and opportunities for statisticians. Statistical inference in observational studies and many other emerging fields have motivated statisticians worldwide to develop cutting-edge methods and analytical strategies. The aim of this reprin...
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Format: | Electronic Book Chapter |
Language: | English |
Published: |
Basel
MDPI - Multidisciplinary Digital Publishing Institute
2023
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Online Access: | DOAB: download the publication DOAB: description of the publication |
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001 | doab_20_500_12854_100876 | ||
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020 | |a books978-3-0365-7547-6 | ||
020 | |a 9783036575469 | ||
020 | |a 9783036575476 | ||
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024 | 7 | |a 10.3390/books978-3-0365-7547-6 |c doi | |
041 | 0 | |a eng | |
042 | |a dc | ||
072 | 7 | |a KNTX |2 bicssc | |
072 | 7 | |a UY |2 bicssc | |
100 | 1 | |a Ferreira, Sandra |4 edt | |
700 | 1 | |a Ferreira, Sandra |4 oth | |
245 | 1 | 0 | |a Computational Mathematics and Applied Statistics |
260 | |a Basel |b MDPI - Multidisciplinary Digital Publishing Institute |c 2023 | ||
300 | |a 1 electronic resource (334 p.) | ||
336 | |a text |b txt |2 rdacontent | ||
337 | |a computer |b c |2 rdamedia | ||
338 | |a online resource |b cr |2 rdacarrier | ||
506 | 0 | |a Open Access |2 star |f Unrestricted online access | |
520 | |a Rapid advances in modelling research have created new challenges and opportunities for statisticians. Statistical inference in observational studies and many other emerging fields have motivated statisticians worldwide to develop cutting-edge methods and analytical strategies. The aim of this reprint is to showcase the applications and methodological research in all fields of computational statistics. This reprint will provide a forum for computer scientists, mathematicians, and statisticians working in a variety of areas in statistics, including biometrics, econometrics, data analysis, graphics, and simulation. | ||
540 | |a Creative Commons |f https://creativecommons.org/licenses/by/4.0/ |2 cc |4 https://creativecommons.org/licenses/by/4.0/ | ||
546 | |a English | ||
650 | 7 | |a Information technology industries |2 bicssc | |
650 | 7 | |a Computer science |2 bicssc | |
653 | |a descriptive statistics | ||
653 | |a inferential statistics | ||
653 | |a species abundance data plots | ||
653 | |a abundance models | ||
653 | |a species richness indices | ||
653 | |a diversity measures | ||
653 | |a sampling | ||
653 | |a community comparisons | ||
653 | |a diversity in space (time) | ||
653 | |a extreme value modeling | ||
653 | |a epidemiology | ||
653 | |a adaptive sampling | ||
653 | |a trend analysis | ||
653 | |a ecological modeling | ||
653 | |a detection limit | ||
653 | |a Pseudo Lindley distribution | ||
653 | |a survival discretization method | ||
653 | |a over dispersion | ||
653 | |a moments | ||
653 | |a simulation | ||
653 | |a maximum likelihood estimation | ||
653 | |a goodness-of-fit | ||
653 | |a trigonometric distributions | ||
653 | |a modified Lindley distribution | ||
653 | |a engineering data | ||
653 | |a climate data | ||
653 | |a statistical analysis | ||
653 | |a Burr III distribution | ||
653 | |a stochastic ordering | ||
653 | |a middle-censoring | ||
653 | |a order statistics | ||
653 | |a Teissier distribution | ||
653 | |a unit Teissier distribution | ||
653 | |a Lambert W function | ||
653 | |a entropy | ||
653 | |a extropy | ||
653 | |a estimation | ||
653 | |a compounding distributions | ||
653 | |a Lindley distribution | ||
653 | |a Lomax distribution | ||
653 | |a stress strength model | ||
653 | |a characterization | ||
653 | |a Nadarajah-Haghighi distribution | ||
653 | |a data analysis | ||
653 | |a evaporation | ||
653 | |a adaptive neuro fuzzy system | ||
653 | |a firefly algorithm | ||
653 | |a particle swarm optimization | ||
653 | |a genetic algorithm | ||
653 | |a statistical indices | ||
653 | |a Euclidean distance timed and spaced | ||
653 | |a meteorological station | ||
653 | |a multivariable panel data cluster analysis | ||
653 | |a biomedical data | ||
653 | |a trigonometric function | ||
653 | |a continuous distribution | ||
653 | |a undernutrition | ||
653 | |a prevalence | ||
653 | |a hierarchical Bayesian | ||
653 | |a spatial analysis | ||
653 | |a small area estimation | ||
653 | |a Markov chain Monte Carlo | ||
653 | |a wavelet analysis | ||
653 | |a extreme subtropical cyclones | ||
653 | |a climate change | ||
653 | |a sea surface temperature anomalies | ||
653 | |a oceanic Rossby waves | ||
653 | |a Marine Heatwaves | ||
653 | |a Gerber-Shiu function | ||
653 | |a constant force of interest | ||
653 | |a Volterra equation | ||
653 | |a absolute ruin | ||
653 | |a delayed reporting times | ||
653 | |a generalized odd linear distribution | ||
653 | |a hazard rate function | ||
653 | |a residual analysis | ||
653 | |a Monte Carlo simulation | ||
653 | |a Prony method | ||
653 | |a exponential sums | ||
653 | |a eigenfunctions | ||
653 | |a eigenvalues | ||
653 | |a sparse expansion | ||
653 | |a generating function | ||
653 | |a Hankel matrix | ||
653 | |a short time Fourier transform | ||
653 | |a least-square method | ||
653 | |a bivariate beta | ||
653 | |a gamma | ||
653 | |a hypergeometric function | ||
653 | |a sequential | ||
653 | |a shift in process variance | ||
653 | |a discretizing | ||
653 | |a natural discrete Lindley distribution | ||
653 | |a n/a | ||
856 | 4 | 0 | |a www.oapen.org |u https://mdpi.com/books/pdfview/book/7340 |7 0 |z DOAB: download the publication |
856 | 4 | 0 | |a www.oapen.org |u https://directory.doabooks.org/handle/20.500.12854/100876 |7 0 |z DOAB: description of the publication |