LEADER 03301oam 2200661I 450 001 9910451309703321 005 20200520144314.0 010 $a1-134-37475-5 010 $a1-281-10083-8 010 $a9786611100834 010 $a0-203-93009-6 024 7 $a10.4324/9780203930090 035 $a(CKB)1000000000406990 035 $a(EBL)331037 035 $a(OCoLC)476130131 035 $a(SSID)ssj0000270366 035 $a(PQKBManifestationID)11206357 035 $a(PQKBTitleCode)TC0000270366 035 $a(PQKBWorkID)10261680 035 $a(PQKB)10598194 035 $a(MiAaPQ)EBC331037 035 $a(Au-PeEL)EBL331037 035 $a(CaPaEBR)ebr10205117 035 $a(CaONFJC)MIL110083 035 $a(OCoLC)191813759 035 $a(EXLCZ)991000000000406990 100 $a20180706d2003 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aWestern civilization in world history /$fPeter N. Stearns 210 1$aNew York :$cRoutledge,$d2003. 215 $a1 online resource (145 p.) 225 1 $aThemes in world history 300 $aDescription based upon print version of record. 311 $a0-415-31610-3 311 $a0-415-31611-1 320 $aIncludes bibliographical references and index. 327 $aBook Cover; Title; Copyright; Contents; Acknowledgments; Chapter 1 Introduction: Why Western civ?; Part I: The Western civ tradition; Chapter 2 Why Western civ courses: The constraints of success; Chapter 3 The fall of Western civ, and why it still stands; Part II: Getting Western civilization started; Chapter 4 Defining civilizations; Chapter 5 When in the world is Western civilization?; Chapter 6 The West in the world; Part III: The rise of the West, 1450-1850; Chapter 7 Causes of a new global role; Chapter 8 Transformations of the West 327 $aChapter 9 Where in the world was Western civilization?Part IV: The West in the contemporary world; Chapter 10 Western civilization and the industrial revolution; Chapter 11 Disruptions of the twentieth century; Chapter 12 The West in a globalized world; Epilogue: Western civilization and Western civ; Index 330 $aWestern civilization and world history are often seen as different, or even mutually exclusive, routes into historical studies. This volume shows that they can be successfully linked, providing a tool to see each subject in the context of the other, identifying influences and connections.Western Civilization in World History takes up the recent debates about the merits of the well-established 'Western civ' approach versus the newer field of world history. Peter N. Stearns outlines key aspects of Western civilization - often assumed rather than analyzed - and reviews them in 410 0$aThemes in world history. 606 $aCivilization, Western$xHistory 606 $aWorld history 608 $aElectronic books. 615 0$aCivilization, Western$xHistory. 615 0$aWorld history. 676 $a909/.09821 686 $a15.50$2bcl 700 $aStearns$b Peter N.$0183190 801 0$bFlBoTFG 801 1$bFlBoTFG 906 $aBOOK 912 $a9910451309703321 996 $aWestern civilization in world history$92078974 997 $aUNINA LEADER 03910nam 2200961z- 450 001 9910557660803321 005 20210501 035 $a(CKB)5400000000044898 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/68741 035 $a(oapen)doab68741 035 $a(oapen)68741 035 $a(EXLCZ)995400000000044898 100 $a20202105d2020 |y 0 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aMachine Learning in Insurance 210 $aBasel, Switzerland$cMDPI - Multidisciplinary Digital Publishing Institute$d2020 215 $a1 online resource (260 p.) 311 08$a3-03936-447-2 311 08$a3-03936-448-0 330 $aMachine learning is a relatively new field, without a unanimous definition. In many ways, actuaries have been machine learners. In both pricing and reserving, but also more recently in capital modelling, actuaries have combined statistical methodology with a deep understanding of the problem at hand and how any solution may affect the company and its customers. One aspect that has, perhaps, not been so well developed among actuaries is validation. Discussions among actuaries' "preferred methods" were often without solid scientific arguments, including validation of the case at hand. Through this collection, we aim to promote a good practice of machine learning in insurance, considering the following three key issues: a) who is the client, or sponsor, or otherwise interested real-life target of the study? b) The reason for working with a particular data set and a clarification of the available extra knowledge, that we also call prior knowledge, besides the data set alone. c) A mathematical statistical argument for the validation procedure. 606 $aHistory of engineering and technology$2bicssc 610 $aaccelerated failure time model 610 $aanalyzing financial data 610 $aautocorrelation 610 $aautomobile insurance 610 $abenchmark 610 $aBornhuetter-Ferguson 610 $acalibration 610 $acanonical parameters 610 $achain ladder 610 $achain-ladder method 610 $aclaims prediction 610 $across-validation 610 $adeposit insurance 610 $adichotomous response 610 $aexponential families 610 $aexport credit insurance 610 $ageneralised linear modelling 610 $aGLM 610 $aimplied volatility 610 $aleast-squares monte carlo method 610 $alife insurance 610 $alocal linear kernel estimation 610 $along-term forecasts 610 $amachine learning 610 $amaximum likelihood 610 $an/a 610 $anon-life reserving 610 $aoperational time 610 $aoverdispersion 610 $aoverlapping returns 610 $aparameterization 610 $aprediction 610 $apredictive model 610 $aprior knowledge 610 $aproxy modeling 610 $arisk classification 610 $arisk selection 610 $asemiparametric modeling 610 $aSolvency II 610 $astatic arbitrage 610 $astock return volatility 610 $atelematics 610 $atree boosting 610 $avalidation 610 $aVaR estimation 610 $azero-inflated poisson model 610 $azero-inflation 615 7$aHistory of engineering and technology 700 $aNielsen$b Jens Perch$4edt$01314788 702 $aAsimit$b Alexandru$4edt 702 $aKyriakou$b Ioannis$4edt 702 $aNielsen$b Jens Perch$4oth 702 $aAsimit$b Alexandru$4oth 702 $aKyriakou$b Ioannis$4oth 906 $aBOOK 912 $a9910557660803321 996 $aMachine Learning in Insurance$93031967 997 $aUNINA