000 | 02624nam a2200361 i 4500 | ||
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001 | CR9781108649841 | ||
003 | UkCbUP | ||
005 | 20240807184505.0 | ||
006 | m|||||o||d|||||||| | ||
007 | cr|||||||||||| | ||
008 | 180717s2019||||enk o ||1 0|eng|d | ||
020 | _a9781108649841 (ebook) | ||
020 | _z9781108483407 (hardback) | ||
040 |
_aUkCbUP _beng _erda _cUkCbUP |
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050 | 0 | 0 |
_aHB139 _b.R3292 2019 |
082 | 0 | 0 |
_a330.01/51954 _223 |
100 | 1 |
_aRacine, Jeffrey Scott, _d1962- _eauthor. |
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245 | 1 | 3 |
_aAn introduction to the advanced theory of nonparametric econometrics : _ba replicable approach using R / _cJeffrey S. Racine. |
264 | 1 |
_aCambridge : _bCambridge University Press, _c2019. |
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300 |
_a1 online resource (xxvi, 408 pages) : _bdigital, PDF file(s). |
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336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
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338 |
_aonline resource _bcr _2rdacarrier |
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500 | _aTitle from publisher's bibliographic system (viewed on 26 Mar 2019). | ||
505 | 0 | _aDiscrete probability and cumulative probability functions -- Continuous density and cumulative distribution functions -- Mixed-data probability density and cumulative distribution functions -- Conditional probability density and cumulative distribution functions -- Conditional moment functions -- Conditional mean function estimation -- Conditional mean function estimation with endogenous predictors -- Semiparametric conditional mean function estimation -- Conditional variance function estimation. | |
520 | _aInterest in nonparametric methodology has grown considerably over the past few decades, stemming in part from vast improvements in computer hardware and the availability of new software that allows practitioners to take full advantage of these numerically intensive methods. This book is written for advanced undergraduate students, intermediate graduate students, and faculty, and provides a complete teaching and learning course at a more accessible level of theoretical rigor than Racine's earlier book co-authored with Qi Li, Nonparametric Econometrics: Theory and Practice (2007). The open source R platform for statistical computing and graphics is used throughout in conjunction with the R package np. Recent developments in reproducible research is emphasized throughout with appendices devoted to helping the reader get up to speed with R, R Markdown, TeX and Git. | ||
650 | 0 | _aEconometrics. | |
650 | 0 | _aNonparametric statistics. | |
650 | 0 | _aR (Computer program language) | |
776 | 0 | 8 |
_iPrint version: _z9781108483407 |
856 | 4 | 0 | _uhttps://doi.org/10.1017/9781108649841 |
942 |
_2ddc _cEB |
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999 |
_c9697 _d9697 |