ࡱ> ;=: RxbjbjWW2"558NbD`bbbbbb$;d-4``P(9odFL0hJ, :  zTy ;NYe^ w zI 6g30-7g1eAnalysis of Censored Data Danyu Lin, University of North Carolina, Chapel Hill w zII 7g2-3eMultiple Testing: Theory and Applications Frank Bretz Novartis w zIII 7g3-4eSome topics in the empirical likelihoodJiahua Chen, University of British Columbia, Canada w z IV 7g6-7eCausal inference and related topics in Biostatistics Menggang Yu, University of Wisconsin-Madison, USA w z V 7g7-8eRisk Measures and Optimal Reinsurance Designs Jun Cai, University of Univer $&(*246:npN P f j | ~ V X Z b h j l n t x H J L T X Z \ ^ d h ョョョョョh@(CJaJh+h@(CJOJ^JaJ"h+h@(5CJOJ\^JaJ&h+h@(5CJOJPJ\^JaJh@(CJOJ^JaJ h+h@(CJOJPJ^JaJ@ &:pjXXXX$&P#$/Ifgd@(kd$$Iflm0)7 6P0*4 laytR8X$$&P#$/Ifa$gd@(P ~ lZZZZ$&P#$/Ifgd@(kd$$Ifl!F)  6P0*    4 laytQ~ X lZZZZ$&P#$/Ifgd@(kdh$$Ifl!F)  6P0*    4 laytQX Z j x J lZZZZ$&P#$/Ifgd@(kd#$$Ifl!F)  6P0*    4 laytQJ L Z h 4lZZZZ$&P#$/Ifgd@(kd$$Ifl!F)  6P0*    4 laytQsity of Waterloo, Canada w z VI 7g9 -10eIntroduction to big data analysis and statistical learning Sijian Wang, University of Wisconsin-Madison, USA  z[c 246>DFHJTX468:DFJLPRVX\^`bdfhjlnprtvxïïïԪh."hhijhiUh@(h@(5CJaJo( hdso(&h+h@(5CJOJPJ\^JaJ h+h@(CJOJPJ^JaJh@(CJaJh+h@(CJOJ^JaJ"h+h@(5CJOJ\^JaJU(46FX6lZZZZ$&P#$/Ifgd@(kd$$Ifl!F)  6P0*    4 laytQ68:DHJNPTVZlg_]]]]]]]$a$gd@(gd@(kdT$$Ifl!F)  6P0*    4 laytQ Z\^`bdfhjlnprtvx$a$gd@(&dPgd0&P 18. A!"#Q$n%S $$If!vh#v7#v :V lm6P0*575 / 4ytR8X$$If!vh#v#v #v :V l!6P0*55 5 / 4ytQ$$If!vh#v#v #v :V l!6P0*55 5 / 4ytQ$$If!vh#v#v #v :V l!6P0*55 5 / 4ytQ$$If!vh#v#v #v :V l!6P0*55 5 / 4ytQ$$If!vh#v#v #v :V l!6P0*55 5 / 4ytQ$$If!vh#v#v #v :V l!6P0*55 5 / 4ytQb 2 0@P`p2( 0@P`p 0@P`p 0@P`p 0@P`p 0@P`p 0@P`p8XV~PJ_HmH nHsH tHJ`J cke $1$a$ CJKH_HaJmH nHsH tH$A $ ؞k=W[SOFi@F nfhxjm)ʬuWLfdݮ+5_4csj-V?k3rm}gzgs嚋7xwsȈR W*)|jȫKXͫ dXIBF؇bnh ( *'vɗ3KZjz'c*_=}<9ݻw~]8^~_o?xYýg~^G}J0Emh=Ԅ Ξa>s$-, Oɠ=Hp Ua/ UO d*:(.fTU/!9$V[|hrvs-iUt. 6ڪ4Cebs)bMjBekp um,fd$͑{6GUVf~b#Vb@qTTW.ޛd)i@vdq9Y^X7{2%uHx+af6]>f#sm*qqDHehK)@?71oggo`:fղekp£2֌Nj8ǰD CB?81e>nEeU}H]dm1iQ6褣֧ "  x~ X J 46Zx @ @H 0(  0(  B S  ? 8=orwx{|-067:;rz$%*+hn8o}-<,Q&Im6R8Xd>!-!),.:;?]}    & 6"0000 0 000000 =@\]^([{  0 0 00000;[Qr 3qHX ?z2!xx WSN'Yf[ -N'kklhQVxvzufgf[!h juV_o(u7bOh+'0   4@ ` l x,ϾѧŷȽϷȫоѧУ ѻ԰ Normal.dotm ΢û10Microsoft Office Word@G@%@^@ Rod>՜.+,0 X` Microsoft Corporation   !"#$%&'()+,-./013456789<Root Entry FP-9o>Data 1TableWordDocument2"SummaryInformation(*DocumentSummaryInformation82CompObjn  FMicrosoft Word 97-2003 ĵ MSWordDocWord.Document.89q RxbjbjWW2"558NbD`bbbbbb$;d-4``P(9odFL0hJ, :  zTy ;NYe^ w zI 6g30-7g1eAnalysis of Censored Data Danyu Lin, University of North Carolina, Chapel Hill w zII 7g2-3eMultiple Testing: Theory and Applications Frank Bretz Novartis w zIII 7g3-4eSome topics in the empirical likelihoodJiahua Chen, University of British Columbia, Canada w z IV 7g6-7eCausal inference and related topics in Biostatistics Menggang Yu, University of Wisconsin-Madison, USA w z V 7g7-8eRisk Measures and Optimal Reinsurance Designs Jun Cai, University of Univer $&(*246:npN P f j | ~ V X Z b h j l n t x H J L T X Z \ ^ d h ョョョョョh@(CJaJh+h@(CJOJ^JaJ"h+h@(5CJOJ\^JaJ&h+h@(5CJOJPJ\^JaJh@(CJOJ^JaJ h+h@(CJOJPJ^JaJ@ &:pjXXXX$&P#$/Ifgd@(kd$$Iflm0)7 6P0*4 laytR8X$$&P#$/Ifa$gd@(P ~ lZZZZ$&P#$/Ifgd@(kd$$Ifl!F)  6P0*    4 laytQ~ X lZZZZ$&P#$/Ifgd@(kdh$$Ifl!F)  6P0*    4 laytQX Z j x J lZZZZ$&P#$/Ifgd@(kd#$$Ifl!F)  6P0*    4 laytQJ L Z h 4lZZZZ$&P#$/Ifgd@(kd$$Ifl!F)  6P0*    4 laytQsity of Waterloo, Canada w z VI 7g9 -10eIntroduction to big data analysis and statistical learning Sijian Wang, University of Wisconsin-Madison, USA  z[c 246>DFHJTX468:DFJLPRVX\^`bdfhjlnprtvxïïïԪh."hhijhiUh@(h@(5CJaJo( hdso(&h+h@(5CJOJPJ\^JaJ h+h@(CJOJPJ^JaJh@(CJaJh+h@(CJOJ^JaJ"h+h@(5CJOJ\^JaJU(46FX6lZZZZ$&P#$/Ifgd@(kd$$Ifl!F)  6P0*    4 laytQ68:DHJNPTVZlg_]]]]]]]$a$gd@(gd@(kdT$$Ifl!F)  6P0*    4 laytQ Z\^`bdfhjlnprtvx$a$gd@(&dPgd0&P 18. A!"#Q$n%S $$If!vh#v7#v :V lm6P0*575 / 4ytR8X$$If!vh#v#v #v :V l!6P0*55 5 / 4ytQ$$If!vh#v#v #v :V l!6P0*55 5 / 4ytQ$$If!vh#v#v #v :V l!6P0*55 5 / 4ytQ$$If!vh#v#v #v :V l!6P0*55 5 / 4ytQ$$If!vh#v#v #v :V l!6P0*55 5 / 4ytQ$$If!vh#v#v #v :V l!6P0*55 5 / 4ytQb 2 0@P`p2( 0@P`p 0@P`p 0@P`p 0@P`p 0@P`p 0@P`p8XV~PJ_HmH nHsH tHJ`J cke $1$a$ CJKH_HaJmH nHsH tH$A $ ؞k=W[SOFi@F nfhxjm)ʬuWLfdݮ+5_4csj-V?k3rm}gzgs嚋7xwsȈR W*)|jȫKXͫ dXIBF؇bnh ( *'vɗ3KZjz'c*_=}<9ݻw~]8^~_o?xYýg~^G}J0Emh=Ԅ Ξa>s$-, Oɠ=Hp Ua/ UO d*:(.fTU/!9$V[|hrvs-iUt. 6ڪ4Cebs)bMjBekp um,fd$͑{6GUVf~b#Vb@qTTW.ޛd)i@vdq9Y^X7{2%uHx+af6]>f#sm*qqDHehK)@?71oggo`:fղekp£2֌Nj8ǰD CB?81e>nEeU}H]dm1iQ6褣֧ "  x~ X J 46Zx @ @H 0(  0(  B S  ? 8=orwx{|-067:;rz$%*+hn8o}-<,Q&Im6R8Xd>!-!),.:;?]}    & 6"0000 0 000000 =@\]^([{  0 0 00000;[Qr 3qHX ?z2!xx WSN'Yf[ -N'kklhQVxvzufgf[!h juV_o(u7bOh+'0   4@ ` l x,ϾѧŷȽϷȫоѧУ ѻ԰ Normal.dotm ΢û10Microsoft Office Word@G@%@^@ Rod>՜.+,0 X` Microsoft Corporation   !"#$%&'()+,-./013456789<Root Entry FP-9o>Data 1TableWordDocument2"SummaryInformation(*DocumentSummaryInformation82CompObjn  FMicrosoft Word 97-2003 ĵ MSWordDocWord.Document.89q