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- Author: Soubhik Chakraborty
- Publisher: GRIN Verlag
- Year: 2019
- Pages: 68
- ISBN-10: 3668965099
- ISBN-13: 9783668965096
- Format: 14.8 x 21 x 0.4 cm, minkšti viršeliai
- Language: English
- SAVE -10% with code: EXTRA
Probabilistic Analysis of a Random Determinant (e-book) (used book) | bookbook.eu
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Master's Thesis from the year 2019 in the subject Mathematics - Stochastics, grade: 8.5, course: Integrated MSc in Mathematics and Computing, language: English, abstract: We are interested in the behaviour of a determinant with i.i.d. random variates as its elements. A probabilistic analysis has been done for such determinants of orders 2 and 3. We have considered some of the well known distributions, namely, discrete uniform, Binomial Poisson, continuous uniform, standard normal, standard Cauchy and exponential. We are able to give fiducial limits for the determinant using Chebyshev's inequality for all the distributions discussed in the text (except standard Cauchy distribution for which expectation does not exist). The main objective is to find the probability distribution of the determinant when its elements are from any of the distributions stated above. The desired distribution has been approximated using the method of transformation in general but when this method could not produce desired results we relied on empirical results based on simulation.
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- Author: Soubhik Chakraborty
- Publisher: GRIN Verlag
- Year: 2019
- Pages: 68
- ISBN-10: 3668965099
- ISBN-13: 9783668965096
- Format: 14.8 x 21 x 0.4 cm, minkšti viršeliai
- Language: English English
Master's Thesis from the year 2019 in the subject Mathematics - Stochastics, grade: 8.5, course: Integrated MSc in Mathematics and Computing, language: English, abstract: We are interested in the behaviour of a determinant with i.i.d. random variates as its elements. A probabilistic analysis has been done for such determinants of orders 2 and 3. We have considered some of the well known distributions, namely, discrete uniform, Binomial Poisson, continuous uniform, standard normal, standard Cauchy and exponential. We are able to give fiducial limits for the determinant using Chebyshev's inequality for all the distributions discussed in the text (except standard Cauchy distribution for which expectation does not exist). The main objective is to find the probability distribution of the determinant when its elements are from any of the distributions stated above. The desired distribution has been approximated using the method of transformation in general but when this method could not produce desired results we relied on empirical results based on simulation.
Reviews