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008 | 150903s2013 xxu| o |||| 0|eng d | ||
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_a9781461464433 _99781461464433 |
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_a10.1007/9781461464433 _2doi |
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_a201509030342 _bVLOAD _c201405050235 _dVLOAD _y201402061113 _zstaff |
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_aMX-SnUAN _bspa _cMX-SnUAN _erda |
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050 | 4 | _aQA276-280 | |
100 | 1 |
_aDesai, Tejas. _eautor _9317510 |
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245 | 1 | 2 |
_aA Multiple-Testing Approach to the Multivariate Behrens-Fisher Problem : _bwith Simulations and Examples in SAS® / _cby Tejas Desai. |
264 | 1 |
_aNew York, NY : _bSpringer New York : _bImprint: Springer, _c2013. |
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_av, 55 páginas _brecurso en línea. |
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_atexto _btxt _2rdacontent |
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_acomputadora _bc _2rdamedia |
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_arecurso en línea _bcr _2rdacarrier |
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_aarchivo de texto _bPDF _2rda |
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490 | 0 |
_aSpringerBriefs in Statistics, _x2191-544X |
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500 | _aSpringer eBooks | ||
505 | 0 | _aIntroduction -- On Testing for Multivariate Normality -- On Testing Equality of Covariance Matrices -- On Heteroscedastic MANOVA -- References. | |
520 | _a In statistics, the Behrens–Fisher problem is the problem of interval estimation and hypothesis testing concerning the difference between the means of two normally distributed populations when the variances of the two populations are not assumed to be equal, based on two independent samples. In his 1935 paper, Fisher outlined an approach to the Behrens-Fisher problem. Since high-speed computers were not available in Fisher’s time, this approach was not implementable and was soon forgotten. Fortunately, now that high-speed computers are available, this approach can easily be implemented using just a desktop or a laptop computer. Furthermore, Fisher’s approach was proposed for univariate samples. But this approach can also be generalized to the multivariate case. In this monograph, we present the solution to the afore-mentioned multivariate generalization of the Behrens-Fisher problem. We start out by presenting a test of multivariate normality, proceed to test(s) of equality of covariance matrices, and end with our solution to the multivariate Behrens-Fisher problem. All methods proposed in this monograph will be include both the randomly-incomplete-data case as well as the complete-data case. Moreover, all methods considered in this monograph will be tested using both simulations and examples. | ||
590 | _aPara consulta fuera de la UANL se requiere clave de acceso remoto. | ||
710 | 2 |
_aSpringerLink (Servicio en línea) _9299170 |
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_iEdición impresa: _z9781461464426 |
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_uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/978-1-4614-6443-3 _zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL) |
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