LEADER 00776nam0-22002891i-450- 001 990000459350403321 005 20001010 035 $a000045935 035 $aFED01000045935 035 $a(Aleph)000045935FED01 035 $a000045935 100 $a20001010d--------km-y0itay50------ba 101 0 $aita 105 $ay-------001yy 200 1 $aComputer sciences and applied mathemati cs. Vol. 2. Digital picture processing.$fA. Rosenfeld, A.C. Kak. - 205 $aSec. Ed. 210 $aFlorida$cAc. Pr. Inc.$d1982 676 $a 700 1$aRosenfled,$bA. 702 1$aKak,$bAvinash C. 801 0$aIT$bUNINA$gRICA$2UNIMARC 901 $aBK 912 $a990000459350403321 952 $a10 I 59$b155 DIS$fDINEL 959 $aDINEL 997 $aUNINA DB $aING01 LEADER 02035nam 2200409 450 001 9910811300903321 005 20230124200850.0 010 $a1-68140-874-0 035 $a(CKB)4100000011917867 035 $a(MiAaPQ)EBC6577327 035 $a(Au-PeEL)EBL6577327 035 $a(OCoLC)1249470932 035 $a(EXLCZ)994100000011917867 100 $a20220601d2020 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aPicture-perfect lecciones de ciencia, segunda edicion ampliada $ecomo utilizar manuales infantiles para guiar la investigacion, 3-6 /$fEmily Morgan, Karen Ansberry 210 1$aArlington, Virginia :$cNational Science Teachers Association,$d[2020] 210 4$d©2020 215 $a1 online resource (187 pages) 311 $a1-68140-863-5 327 $aFront Cover -- Contenidos -- Reconocimientos -- Acerca de las Autoras -- Medidas de seguridad para las actividades de ciencia -- 6 - Sabuesos de la tierra -- 7- ¡Dale un nombre a esa concha marina! -- 8 - El arroz es vida -- 9 - ¿Que? pasa? -- 10 - Buhos misteriosos -- 11 - Encuentros cercanos del tipo simbio?tico -- 12 - Los obsta?culos de la tortuga -- 13 - ¡Derrame de petroleo! -- 14 - Ovejas en un vehi?culo todo terreno -- 15 - Los sonidos de la ciencia -- 16 - Cambios qui?mico en el cafe? -- 17 - La luna cambiante -- 18 - El di?a y la noche -- 19 - El Gran Can?o?n -- 20 - Propuestas de ideas: De la idea al invento -- 21 - ¡Insectos! -- 22 - Bateri?as incluidas -- 23 - Los secretos de volar -- 24 - Por el resumidero -- 25 - Si construyo un auto -- Untitled. 606 $aScience 615 0$aScience. 676 $a500 700 $aMorgan$b Emily$01660222 702 $aAnsberry$b Karen 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910811300903321 996 $aPicture-perfect lecciones de ciencia, segunda edicion ampliada$94086332 997 $aUNINA LEADER 04079nam 22007455 450 001 9910438030503321 005 20250410121714.0 010 $a3-319-00840-4 024 7 $a10.1007/978-3-319-00840-0 035 $a(CKB)3710000000019087 035 $a(EBL)1474340 035 $a(OCoLC)861528599 035 $a(SSID)ssj0001010524 035 $a(PQKBManifestationID)11577423 035 $a(PQKBTitleCode)TC0001010524 035 $a(PQKBWorkID)10999468 035 $a(PQKB)10896809 035 $a(DE-He213)978-3-319-00840-0 035 $a(MiAaPQ)EBC1474340 035 $a(PPN)17242299X 035 $a(EXLCZ)993710000000019087 100 $a20130903d2013 u| 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aRobustness in Statistical Forecasting /$fby Yuriy Kharin 205 $a1st ed. 2013. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2013. 215 $a1 online resource (369 p.) 300 $aDescription based upon print version of record. 311 08$a3-319-00839-0 320 $aIncludes bibliographical references and index. 327 $aPreface -- Symbols and Abbreviations -- Introduction -- A Decision-Theoretic Approach to Forecasting -- Time Series Models of Statistical Forecasting -- Performance and Robustness Characteristics in Statistical Forecasting -- Forecasting under Regression Models of Time Series -- Robustness of Time Series Forecasting Based on Regression Models -- Optimality and Robustness of ARIMA Forecasting -- Optimality and Robustness of Vector Autoregression Forecasting under Missing Values -- Robustness of Multivariate Time Series Forecasting Based on Systems of Simultaneous Equations -- Forecasting of Discrete Time Series -- Index. 330 $aTraditional procedures in the statistical forecasting of time series, which are proved to be optimal under the hypothetical model, are often not robust under relatively small distortions (misspecification, outliers, missing values, etc.), leading to actual forecast risks (mean square errors of prediction) that are much higher than the theoretical values. This monograph fills a gap in the literature on robustness in statistical forecasting, offering solutions to the following topical problems: - developing mathematical models and descriptions of typical distortions in applied forecasting problems; - evaluating the robustness for traditional forecasting procedures under distortions; - obtaining the maximal distortion levels that allow the ?safe? use of the traditional forecasting algorithms; - creating new robust forecasting procedures to arrive at risks that are less sensitive to definite distortion types.      . 606 $aStatistics 606 $aProbabilities 606 $aStatistics 606 $aEngineering mathematics 606 $aEngineering$xData processing 606 $aStatistical Theory and Methods 606 $aProbability Theory 606 $aStatistics in Business, Management, Economics, Finance, Insurance 606 $aStatistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences 606 $aMathematical and Computational Engineering Applications 615 0$aStatistics. 615 0$aProbabilities. 615 0$aStatistics. 615 0$aEngineering mathematics. 615 0$aEngineering$xData processing. 615 14$aStatistical Theory and Methods. 615 24$aProbability Theory. 615 24$aStatistics in Business, Management, Economics, Finance, Insurance. 615 24$aStatistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences. 615 24$aMathematical and Computational Engineering Applications. 676 $a330.015195 676 $a519 676 $a519.2 676 $a519.5 700 $aKharin$b Yuriy$4aut$4http://id.loc.gov/vocabulary/relators/aut$01060665 906 $aBOOK 912 $a9910438030503321 996 $aRobustness in Statistical Forecasting$92514807 997 $aUNINA