000 07430cam a2200313Ii 4500
001 9780429078477
008 180706s1991 xx o 000 0 eng d
020 _a9780429078477
_q(e-book : PDF)
020 _z9780824785871
_q(hardback)
024 7 _a10.1201/9781482277098
_2doi
035 _a(OCoLC)1027754329
040 _aFlBoTFG
_cFlBoTFG
_erda
072 7 _aMAT029000
_2bisacsh
100 1 _aBalakrishnan, N.,
_eauthor.
_911139
245 1 0 _aHandbook of the Logistic Distribution /
_cN. Balakrishnan.
250 _aFirst edition.
264 1 _aBoca Raton, FL :
_bCRC Press,
_c1991.
300 _a1 online resource
336 _atext
_2rdacontent
337 _acomputer
_2rdamedia
338 _aonline resource
_2rdacarrier
490 0 _aStatistics: A Series of Textbooks and Monographs
505 0 0 _tchapter 1 Introduction and Historical Remarks --
_tchapter L _.L._. --
_tchapter proximation isdiscussed tostudy the stationary distribution, theabsorption --
_tchapter 2 Logistic Order Statistics and Their Properties --
_t{P(zi)}i-l{1 --
_tchapter E(Zi E(Z7 --
_tchapter = a)I --
_tO<a<1. --
_tchapter + + + + r(i)r(n + + + --
_tchapter = + + + --
_tchapter the resulting equation. get --
_tchapter a: = a: + --
_tchapter moments other than the immediate upper-diagonal product moments, viz., < nand /
_r(-I)k --
_tchapter 31 (_I)/(n /
_r-1)k( --
_tchapter (I -k -1) Il\ --
_tchapter Proof. n --
_tchapter ••(ZI>F] z\\). --
_tchapter 3 Maximum Likelihood Estimation Based on Complete and Type II Censored Samples /
_rN. Balakrishnan --
_tchapter a)/a --
_tchapter e;-[!*(Z,+1:,) ---a --
_t[!*(Z,+1:,) /
_r.!.[_( --
_tchapter P. Zn-where ' -and expressing the --
_tchapter (see Gupta and others, and Chapter 4) by --
_tchapter = = = --
_tchapter n= r = s = --
_tchapter 4 Linear Estimation Based on Complete and Censored /
_rSamples --
_tchapter 4 2 BEST LINEAR UNBIASED ESTIMATION BASED ON CENSORED SAMPLES N. Balakrishnan --
_tchapter I(laT aIT)p-1 --
_tchapter )/u by Gupta, Qureishi, Shah sample sizes (1)5(5)25 rand s. --
_tchapter.) = --
_tchapter = + = --
_tchapter. -. s, --
_tchapter 4 4 ESTIMATION OF QUANTILES USING STATISTICS A. K. Md. Ehsanes Saleh Khatab M. Hassanein --
_tchapter + (u/V3) + (u/V3) /
_r:\\Xi(l --
_tchapter I), --
_tchapter ; r --
_tchapter. =. --
_tchapter K. K, §' K K, K K, K K, K --
_tchapter =. = S' --
_tchapter 5 Reliabil --
_tEstimation Based Complete Censored Samples --
_tchapter U6 fl - --
_tchapter metry of the logistic distribution, have the upper tolerance limit --
_tchapter + t,a, --
_tchapter = + = = --
_tchapter 5 6 ILLUSTRATIVE EXAMPLE --
_tchapter 6 Ranking and Selection Procedures --
_tchapter 0, = --
_tchapter reliability contexts, and a review these provided Gupta --
_tchapter 7 Characterizations --log --
_tchapter statesthat the logistic, andonly thelogistic, distributions have the property --
_tchapter = pr pi --
_tchapter tion, and let 1, be a sequence of sample with distributions --
_tchapter x, y --
_tchapter 8 Translated Families of Distributions --
_tchapter Vjf. Vjf. sVjf. --
_tchapter < If --
_tchapter If Eand 8 --
_t\\I'jf. \\I'jf. --
_tchapter Xp's {X p }. --
_tchapter 9 Univariate Generalized Distributions --
_tchapter (9.3.3) has a solution in a if and only if -2 < b, <, so that the --
_t;;-+l' /
_r;=o:- --
_tchapter same asthe median relative to the ina normally distributed --
_tchapter 10 Some Related Distributions --
_tchapter < < > --
_tchapter 11 Multivariate Logistic Distributions --
_tchapter + p { _ + :2 --
_tchapter. --
_tchapter I <. --
_tchapter 11 4 OF EXTREMES -V --
_tchapter LJ· LJ· --
_tUz-,/ --
_tchapter + + + + --
_tchapter 11 7 FARLlE·GUMBEL·MORGENSTERN DISTRIBUTIONS --
_tchapter Z· Z· --
_tchapter 12 Outlier and Robustness of Estimators --
_tchapter + •• --
_tchapter < s + > x + --
_tchapter for; --
_tchapter x, f(x --
_tchapter 12 5 ROBUSTNESS OF ESTIMATORS OF AND --
_tchapter + 0\ --
_tchapter 12 5.2 Estimators of the Standard Deviation a --
_tchapter = 1)} ' --
_tchapter 13 Goodness-of-Fit Tests --
_tchapter F\ --
_tchapter y= tl = x. --
_tchapter.0.0.0 --
_tchapter 13 4 EXAMPLES OF LOGISTIC PROBABILITY Figure 13.4.1 probability plot of the of the --
_tchapter • • • --
_tchapter 3 2 --
_tchapter 13 9.3 Estimation of by the Ungrouped MLE (tl. /
_r-.!- --
_tchapter = = = = = --
_tchapter 13 10 STATISTICS 13.10.1 Introduction = #(X --
_tchapter G(t) t, -s t :s 1. --
_tchapter W;.• --
_tchapter, :\ --
_tchapter Statistic --
_tHypothesis- --
_tchapter X X\ --
_tchapter + -3 • --
_tchapter n.u.i --
_tchapter APPENDIX VIII. UNI Data Set --
_tchapter 14 Tolerance Limits and Sampling Plans Based on Censored Samples --
_tchapter determining the tolerance limits developed in the earlier sections. 14.2 ONE-SIDED TOLERANCE LIMITS :s :s --
_tchapter _v'3 --
_tchapter = [ { --
_tchapter 14 5 ACCEPTANCE SAMPLING PLANS --
_tchapter 15 Logistic Stochastic Growth Models and Applications --
_tchapter If = --
_tchapter 15 2 SOME STOCHASTIC LOGISTIC GROWTH MODELS --
_tchapter + x + + --
_tchapter = [1'\ --
_tchapter = 1>[1 --
_tchapter + 1] --
_tchapter v =T i /
_r(iZi) --
_tchapter 15 4.2 Absorption Probability Distribution and Moments of First Absorption Times s s Mare --
_tchapter = = = --
_tchapter = t),; = --
_tchapter + = -I, --
_tchapter APPENDIX ':,. i = v=I --
_tchapter 16 Logistic Growth Models and Related Problems --
_tchapter I {y; -f(x;. 6)F --
_tchapter <. s --
_tchapter = \ /
_r-lIa(EC --
_tchapter If.we. --
_tchapter = < = = --
_tchapter m, It --
_tchapter 17 Applications in Health and Social Sciences --
_tchapter =. --
_tIn(::) --
_tchapter ponent anda lack-of-fit component. the model accounts tor the variation --
_tchapter 17 7 GOODNESS-OF FIT TESTS THE LOGISTIC DISTRIBUTION = + )J --
_tchapter 18 Some Other Applications --
_tchapter this section. The data to be analyzed are ornithological data --
_tchapter 18 2.2 Results m-almost --
_tm-a.s --
_tchapter APPENDIX 18.2.A The Log Gamma Distribution --
_tchapter 18 2.B standard generalized logistic --
_tchapter 18 3.2 Estimator of --
_tchapter + '( -')2 --
_tchapter )F, --
_tchapter o : ; = ; = --
_tchapter + rsL. --
_tchapter least-maximum approximant --
_tchapter 18 5.2 Logistic Equation /
_rO<b<l, --
_tchapter reaction, latter external substrata level controls growth --
_tchapter Kumar (l990a). --
_tchapter 8 30-57. --
_tchapter Bibliography --
_tchapter of symmetrically truncated logistic distribution. --
_tchapter erators, --
_tchapter y/nvestigacion Operativa, 3/,232-245. --
_tchapter University Minnesota, Minneapolis, Minnesota. --
_tchapter of the United States and mathematical representation --
_tchapter Ann. --
_tchapter Canadian precipitation data. Suuist., 226. --
_tchapter moments and marginals. Amer. Assoc, 82-86. --
_tchapter Methodology forthedifferential diagnosis complex dataset: A --
_tchapter Author Index --
_tchapter Greenberg, B. G., --
_tchapter Petunin. I. 186.574 Reed. J.• 16.398.424.427. --
_tchapter Tritchler. D. L. 464-466. Walker. S. H., --
_tchapter Subject Index --
_tchapter alized) distribution. samples, 80-82 --
_tchapter functional behavior ofordersta- indifference approach. 151-.
650 0 4 _aStatistical Theory & Methods
_911140
650 0 _aMathematical statistics.
_99597
776 0 8 _iPrint version:
_z9780824785871
_w(DLC) 91035297
856 4 0 _uhttps://www.taylorfrancis.com/books/9781482277098
_zClick here to view.
942 _cEBK
999 _c69889
_d69889