1 SHIMURA Masato polynomial irr.xirr EXCEL irr
|
|
- しげのぶ ちゅうか
- 5 years ago
- Views:
Transcription
1 1 SHIMURA Masato polynomial irr.xirr EXCEL irr d f, pv irr, xirr irr, xirr EXCEL cf cf cf cf calc at once 16 6 References 20 irr, xirr J EXCEL
2 1 2 irr, xirr 1 irr internal rate o f return xirr extended irr xirr 1.1 Example r 100 = r + 5 (1 + r) (1 + r) 3 = 100(1 + r)3 + 5(1 + r) 2 + 5(1 + r) (1 + r) r 295r 2 100r 3 = 0 100(r 3 + 3r 2 + 3r + 1) 5(r 2 + 2r + 1) 5(r + 1) 125 J (p.) ;}. p. 35 _285 _295 _100 _ j _ j_ %( ± ;}. p. _ _ j _ j_
3 1 3 irr, xirr irr _ xirr ,: _ Example r + 305r r 3 = 0 100(r 3 + 3r 2 + 3r + 1) 5(r 2 + 2r + 1) 5(r + 1) 95-5% p. _15 _315 _305 _ _100 _1.5j _1.5j_ _ p. p. p. 35 _285 _295 _ _100 _ j _ j_ xirr xirr ,: _100 _5 _5 95 _0.05
4 polynomial pascal=: 3 : :!/ i. >: y mk_poly_sum=: 3 : 0 NB. make polynominal coefficient. +/ y *."1. pascal <: # y ) pascal # a mk_poly_sum a=. _ _285 _295 _100 mk_poly_sum _100 _5 _5 95 _15 _315 _305 _100 Example mk_poly_sum _ _775 _3900 _10950 _19740 _24150 _20400 _11775 _4450 _995 _ x 3900x x x x x x x 8 995x 9 100x 10 = 0 Example % mk_poly_sum _100 _5 _5 _5 _5 _5 _5 _5 _5 _5 95 _50 _1225 _5100 _13050 _22260 _26250 _21600 _12225 _4550 _1005 _100
5 2 irr.xirr EXCEL =5% 5.0% 5 2 $;}. p. mk_poly_sum _ _2 _ j _ j_ _ j _ j_ _ j _ j_ _ j _ j_ $ ;}.p. mk_poly_sum _100,(9#_5),95 _2 _ j _ j_ _ j _ j_ _ j _ j_ _ j _ j_ _0.05 xirr (i.11),: _100, (9#5), xirr (i.11),: _100, (9#_5),95 _ irr.xirr EXCEL 2.1 irr J irr 3 i f (2 irr=:3 : 0 0 irr y : t=. %>:x cf=.,y tol=. 1e_5 max=. 15 if. 2>#cf do. cash flow must have at least two elements return. end. if. -. *./_1 1 e.*cf do. no sign change in cash flow return. end. cf=. (.cf),:.1.cf*i.#cf while. tol< t-r=. t-%/t#.cf do. t=. r
6 2 irr.xirr EXCEL 6 if. 0=max=. <:max do. iterations exceeded return. end. end. <:%r ) cf=. (.cf),:.1.cf*i.#cf while. tol< t-r=. t-%/t#.cf do. t=. r end. Example a=. _ NB. same Example cf (=a) a1=. (.a),:.1.a*i.#a _ J p. (#.) mk_poly_sum a NB. exact 35 _285 _295 _ x 295x 2 100x 3 1 #. a NB. %/ 1 1- %/ 1 #. a t=1 ) *1 *1 (base) 10 #
7 2 irr.xirr EXCEL d f, pv df xirr df pv df discount factor pv present value (future value) Example data NB. interest.ijs ,:_ NB. time _ NB. pay irr _ xirr ,:_ Present Value pv ,: _ YEAR CF DF PV 0 _100 1 _ _ 100 df (discount factor) 1 (1 + irr) i df ,:_ calc_poly_sum _ mk_poly_sum _ # NB # J Vocaburaly #.y is a weighted sum of the items of y that is, +/w*y where w is the product scan */\.}.x,1
8 2 irr.xirr EXCEL 8 35 _285 _295 _ x 295x 2 100x 3 = Script df=:3 : 0 NB. discount factor NB. 1/(1+irr)ˆi NB. Usage: (df/xirr) ,:_ %(>:xirr y)ˆi. # {.y ) pv_sub0=:3 : 0 NB. Usage: (pv_sub/df/xirr) ,:_ tmp=.(;{: y),. df y tmp=.(i.# tmp),.tmp,. _,}. */"1 tmp tmp, _,_,_,{:+/}.tmp ) 2.3 irr, xirr irr, xirr mk poly sum irr, xirr. irr _100, 9#5 _ xirr (i.10),: _100, 9#5 _ mk poluy sum. mk_poly_sum _100, 9#5 _55 _720 _3180 _7770 _11970 _12180 _8220 _3555 _895 _100,.;}. p. mk_poly_sum _100, 9#5 _ j
9 2 irr.xirr EXCEL 9 _ j_ _ j _ j_ _ j _ j_ _ j _ j_ _ irr, xirr irr, xirr J irr, xirr J irr, xirr xirr (i.11),: _100,10#_5 no sign change in cash flow xirr (i.11),: _100,10#_5 iterations exceeded mk poly sum mk_poly_sum 10 mk_poly_sum _100, 10#_5 _150 _1225 _5100 _13050 _22260 _26250 _21600 _12225 _4550 _1005 _100 p. p.!! 5 2 $ ;}. p. mk_poly_sum _100, 10#_5 _1.6737j _1.6737j_ _ j _ j_ _ j _ j_ _ j _ j_ _ j _ j_ $ ;}. p. mk_poly_sum _100, 4#_5
10 2 irr.xirr EXCEL 10 _ j _ j_ _ j _ j_ irr _100, 9#_5 no sign change in cash flow,.;}. p. mk_poly_sum _100, 9#_5 _ _ j _ j_ _ j _ j_ _ j _ j_ _ j _ j_ Example. 1 + r = n (1 + r 1 )(1 + r 2 )(1 + r 3 ) (1 + r n ) 1 + r = 4 Π(1.2, 0.9, 1.1, 0.8) = r = % 10000( ) 4 = 9504 NB. check Year (%) calc_geom _ _ _ _
11 2 irr.xirr EXCEL _ _ NB. geometric mean of rate 10000* ˆ4 NB. check NB. check OK Example calc_geom2 _100,(9#5) _ _0.05 _90 _ _85 _ _80 _ _75 _ _70 _ _65 _ _60 _ _55 _ irr irr _100, 9#5 _ r = , r = ( calc_geom2 _100,(9#_5) _ _ _ _ _ _ _ _ _ NB. geametric mean 100* _ ˆ9 _ NB. sum up 9 years
12 EXCEL EXCEL IRR EXCEL =IRR(A0:A4) ganri 100;10 3% nr gankin 100;
13 cf Example %10 3.2% (i.11),:_100, (}: {: : 3 gankin 100;10), _ xirr (i.11),:_100, (}: {: : 3 gankin 100;10), cf Example %10 a=._100 _8 _7.7 _7.4 _7.1 _6.8 _6.5 _6.2 _5.9 _ mk_poly_sum a _66.5 _1324 _5397 _ _22953 _26844 _ _12357 _ _1008 _ $ }.; p. mk_poly_sum a _ _ j _ j_ _1.3106j _1.3106j_ _ j _ j_ _ j _ j_ _ xirr (i.11),:_100 _8 _7.7 _7.4 _7.1 _6.8 _6.5 _6.2 _5.9 _ _ ]r0=. xirr (i.11),: a
14 4 14 _ (1+ r0) -> ˆ Example 4.1 cf Example % % (i.11),: _100,( {: : 3 gankin 100;10) _ xirr (i.11),: _100, 5- ({: : 3 gankin 100;10)-10 _ % xirr (i.61),: _100, 5- ({: : 3 gankin 100;60)-100r cf a1=: _100 _5 _5 115 a2=:_100 _8 _7.7 _7.4 _7.1 _6.8 _6.5 _6.2 _5.9 _ a3=:_100 _8 _7.7 _7.4 _7.1 _6.8 _6.5 _6.2 _5.9 _5.6 34
15 df df(discount factor) df ( ),: _ df a1=. ( ),: _100 _5 _ pv PV(present value) pv ,: _ YEAR CF DF PV 0 _100 1 _ _ fv fv ,: _ YEAR CF ReInvest-Rate FV 1 _ _ future value (df) pv pv ( ),: a1 YEAR CF DF PV 0 _100 1 _ 1 _ _ _ _ _ 100 fv a1= ,: _100 _5 _5 115 YEAR CF ReInvest-Rate FV 1 _100 2 _ _ _ _ _ future value d f = 1 (1 + IRR) i
16 5 calc at once 16 fv (i.11),: a2 YEAR CF ReInvest-Rate FV 1 _100 2 _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ fv (i.11),: a3 YEAR CF ReInvest-Rate FV 1 _100 2 _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ % 10 5% future value 100 0, 5 calc at once y 100 (%) YEAR= NB. years INTEREST= NB. interest rate
17 5 calc at once 17 mk_calc_mat_sub (year rate) mk_calc_mat_sub=: 3 : 0 NB. years interest-rate NB.and profit(except interest rate) YEAR= NB. years INTEREST= NB. interest rate TABLE=. { YEAR;INTEREST ) cf calc_xirr_all=: 3 : 0 NB. Usage:,. calc_xirr_all L:0 {@> NB. y is profit(except interest) per years TABLE=: mk_calc_mat_sub ALL=: }. "1 L:0 ({: L:0 TABLE)gankin (L:0) 100, L:0 {. L:0 TABLE KINRI=: ALL - (L:0) 100 % L:0 {. L:0 TABLE SYUUSI=:_100, L:0 ; L:0 y - L:0 KINRI TABLE2=: (i. L:0 >: L:0 {. L:0 TABLE) ;("1) xirr L:0 TABLE2,: L:0 SYUUSI ) 5% ) calc_xirr_all 5 ( 3% 4% 5% 6%
18 5 calc at once 18 _ _ _ _ NB. 10 years _0.03 _0.04 _0.05 _0.06 NB _ _ _ NB _ _ NB _ NB NB. 60 calc at once %,. calc_xirr_all (L:0){@> ( ) _ _ _ _ NB. 3% _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ NB. 5% _0.03 _0.04 _0.05 _ _ _ _ _ _ _ _ _ _ _ NB. 7% _ _ _ _0.03 _0.04 _0.05 _0.06 NB. 10%
19 5 calc at once
20 6 References 20 6 References 2004 J script Download J602 Script -> APL/J
a b GE(General Erectrics) 9 4 irr (JAPLA 2009/12) Example1 120 P = C r + C 2 (1 + r) C t 1 (1 + r) t 1 + C t + F (1 + r) t 10
1 SHIMURA Masato 2010 9 27 1 1 2 CF 6 3 10 *1 irr irr irr(inner rate of return)function is able to written only few lines,and it is very powerful and useful for simulate unprofitable business model. 1
More information0 2 SHIMURA Masato
0 2 SHIMURA Masato jcd02773@nifty.com 2009 12 8 1 1 1.1................................... 2 1.2.......................................... 3 2 2 3 2.1............................... 3 2.2.......................................
More informationPage
Page Page 1 BIS 200012 2 10 1-2 20003 3 4 1-1 1-2 * BIS CF CF CF PLAN DO BSPL BSPL SEE BS PL 5 6 1-3 PLAN DO SEE PLAN DO SEE PLAN DO SEE PLAN DO SEE BSPL BS PL 4 1-4 7 Coffee Break 2 BS PL CF) PLANDO SEE
More informationR/S.5.72 (LongTerm Strage 1965) NASA (?. 2? (-:2)> 2?.2 NB. -: is half
SHIMURA Masato JCD2773@nifty.ne.jp 29 6 19 1 R/S 1 2 9 3 References 22 C.Reiter 5 1 R/S 1.1 Harold Edwin Hurst 188-1978 England) Leicester, Oxford 3 196 Sir Henry Lyons ( 1915 1946 Hurst Black Simaika
More information1 1.1 p(x n+1 x n, x n 1, x n 2, ) = p(x n+1 x n ) (x n ) (x n+1 ) * (I Q) 1 ( 1 Q 1 Q n 0(n ) I + Q + Q 2 + = (I Q) ] q q +/. * q
Masato Shimura JCD02773@nifty.ne.jp 2008 7 23 1 2 1.1....................................... 2 1.2..................................... 2 2 3 2.1 Example...................................... 3 2.2 Script...........................................
More informationA Message From President 2
A Message From President 2 Top Information 3 Top Information 4 A View Point 5 Annual Report 2 Financial Highlight 7, 5, 12, 6, 5, 4, 3, 2, 1, 4, 3, 2, 1, 1, 8, 6, 4, 2, 6 5, 2, 8 4, 1,5 6 3, 2, 1, 1, 5
More informationExcel97関数編
Excel97 SUM Microsoft Excel 97... 1... 1... 1... 2... 3... 3... 4... 5... 6... 6... 7 SUM... 8... 11 Microsoft Excel 97 AVERAGE MIN MAX SUM IF 2 RANK TODAY ROUND COUNT INT VLOOKUP 1/15 Excel A B C A B
More informationATM M.Shimura JCD02773@nifty.ne.jp 2003 12 13 JAPLA2003 1 queue ATM ATM queue 1.1 ATM No (Sec (Sec 1 13 37 60 26 28 99 1 25 40 39 143 202 14 88 190 27 1 184 2 170 37 40 130 317 15 121 72 28 48 115 3 101
More information28
y i = Z i δ i +ε i ε i δ X y i = X Z i δ i + X ε i [ ] 1 δ ˆ i = Z i X( X X) 1 X Z i [ ] 1 σ ˆ 2 Z i X( X X) 1 X Z i Z i X( X X) 1 X y i σ ˆ 2 ˆ σ 2 = [ ] y i Z ˆ [ i δ i ] 1 y N p i Z i δ ˆ i i RSTAT
More information15 P3 Pm C.Reiter dwin C.Reiter Fractal Visualization and J 4th edition fvj4 J 2D gl2 J addon Appendix (hokusai olympic0.ijs dwin * 1 coinsert *
SHIMURA Masato JCD02773@nifty.ne.jp 2017 2 23 1 2 2 6 3 9 4 15 A J 21 2 3 45 1 15 P3 Pm 1 1.1 C.Reiter dwin C.Reiter Fractal Visualization and J 4th edition fvj4 J 2D gl2 J addon Appendix (hokusai olympic0.ijs
More information40 3 / 3 i i 1 E1 e = E = 4 3 (1) (2) = (3) = (4) = % AA 1.365% % 0.02% 3
39 3 3.1 3 (1) (2) (3)1 3.1 3.1: 2 GDP 3 1 3.2 3.2: / 1 GDP 40 3 / 3 i i 1 E1 e = E 0 3.2 2 2 2 2 = 4 3 (1) (2) = (3) = (4) = 2 2 2010 10 1.187% 10 11 AA 1.365% 10 2011 5 30 0.232% 0.02% 3 3.2. 41 4 2
More informationNo
No. 1 2 No. 3 4 5 6 7 8 9 10 11 12 No. 13 14 15 16 17 18 19 20 21 22 23 24 25 26 No. 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 No. 44 45 46 47 48 49 50 51 52 No. 53 54 55 56 57 58 59 60 61 62
More informationExcel基礎講座演習-表紙とはじめにv1.3.doc
Future Lifestyle Inc. IT Microsoft Excel 2000 Microsoft Microsoft Corporation B4 11 14 1999 1 C4 E7 C4 E7 2 =C4+D4+E4 SUM MAX MIN B3 F7 Sheet2 1999 2000 3 B3 F7 C4 F7 Delete C4 F7 SUM SUM() C4 SUM 4 B3
More informationuntitled
IV2008#005.nb 2. à Black & Scholes ü S K t T t=t - t s : t : : : : : : ü CHtL = SNHd H+L L - K e -HT-tL NHd H-L L d H L ª H lnhs ê KL + H ÅÅÅÅ 2 s2 L HT - tl LëI s è!!!!!!!!! T - t M à (cashflow) cash
More informationPage
Page Page 1 3 4 M&A DCF NPV 1-1 BIS 1-3 1-2 5 6 1-3 2 2 0 200 010 2-1 A B B A B 7 8 Coffee Break CAPM Capital Asset Pricing model 3 IRR NPV EVA BS PL 9 2 ROA 3-1 EBIT Earnings Before Interest,Taxes) 3-2
More information2015-s6-4g-pocket-guidebook_H1-4.indd
56C504-01 2 47 47 32 3435 35 2124 26 26 26 424343 434446 4646 12 14 16 18 20 4 28 30 31 36 37 38 42 47 48 49 4 4 4 3 4 5 16 16 6 6 18 18 32 32 30 30 7 20 20 8 9 28 31 10 Do you have a? 36 Do you have
More informationuntitled
Excel A D-2 B-2 D-2 B2 C-2 D-2 C2-23 - Enter D-2 B2(1000) C2(5) 5000 D-2 (D-2) (D-2) (D-3) (D-6) - 24 - (D-3) (D-6) D (D-2) =B2*C2 (D-3) =B3*C3 (D-4) =B4*C4 Excel - 25 - $A$1 1000 A-1 (B-1) =$A$1 (B-1)
More informationA Message From President 2 Kanamoto examiner vo.18
vol.18 2000.11.1 2001.10.31 contents A Message From President News Headline Report & Interview Annual Report 2001 At A Glance 2 3 4 6 14 Corporate Data Stock Price Range And Volume Investor Information
More information(1)2004年度 日本地理
1 2 3 4 1 2 3 4 5 6 7 8 9 10 11 12-5.0-5.1-1.4 4.2 8.6 12.4 16.9 19.5 16.6 10.8 3.3-2.0 6.6 16.6 16.6 18.6 21.3 23.8 26.6 28.5 28.2 27.2 24.9 21.7 18.4 22.7 5 1 2 3 4 5 6 7 8 9 10 11 12 2.2 3.5 7.7 11.1
More informationJ6 M.Shimura (1) 1 2 (2) (1824) ( (1842) 1 (1) 1.1 C.Reiter dwin require ad
J6 M.Shimura JCD02773@nifty.ne.jp 2011 12 13 1 (1) 1 2 (2)- 12 3 14 4-20 5 24 6 33 60 (1824) ( 100 1760 1849 (1842) 1 (1) 1.1 C.Reiter dwin require addons/graphics/fvj3/dwin2.ijs 1 xy find_maxmin 4 5 calc_each_poly
More informationMicrosoft Word - Win-Outlook.docx
Microsoft Office Outlook での設定方法 (IMAP および POP 編 ) How to set up with Microsoft Office Outlook (IMAP and POP) 0. 事前に https://office365.iii.kyushu-u.ac.jp/login からサインインし 以下の手順で自分の基本アドレスをメモしておいてください Sign
More informationIS-LM (interest) 100 (net rate of interest) (rate of interest) ( ) = 100 (2.1) (gross rate of interest) ( ) = 100 (2.2)
1 2 2 2 2.1 IS-LM 1 2.2 1 1 (interest) 100 (net rate of interest) (rate of interest) ( ) = 100 (2.1) (gross rate of interest) ( ) = 100 (2.2) 1 1. 2. 1 1 ( ) 2.3. 3 2.3 1 (yield to maturity) (rate of return)
More information/
/ 1 UNIX AWK( ) 1.1 AWK AWK AWK A.V.Aho P.J.Weinberger B.W.Kernighan 3 UNIX AWK GNU AWK 1 1.2 1 mkdir ~/data data ( ) cd data 1 98 MS DOS FD 1 2 AWK 2.1 AWK 1 2 1 byte.data 1 byte.data 900 0 750 11 810
More informationキャッシュ・フロー経営とキャッシュ・フロー計算書
No.26 2003 3 Abstract The cash flow taken seriously in the cash flow management is free cash flow. It becomes the purpose of that management that free cash flow will be maximized in the future. The result
More informationh01
P03 P05 P10 P13 P18 P21 1 2 Q A Q A Q A Q A Q A 3 1 check 2 1 2-1 2-2 2-3 2-4 2-5 2-5-1 2-6 2-6-1 2-6-2 2-6-3 3 3-1 3-2 3-3 3-4 3 check 4 5 3-5 3-6 3-7 3-8 3-9 4-1 4-1-1 4-2 4-3 4-4 4-5 4-6 5-1 5-2 4
More information1 2 3 4 1 2 1 2 3 4 5 6 7 8 9 10 11 27 29 32 33 1 2 3 7 9 11 13 15 17 19 21 23 26 CHECK! 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
More information..0.._0807...e.qxp
4 6 0 4 6 0 4 6 8 30 34 36 38 40 4 44 46 8 8 3 3 5 4 6 7 3 4 6 7 5 9 8 3 4 0 3 3 4 3 5 3 4 4 3 4 7 6 3 9 8 Check 3 4 6 5 3 4 0 3 5 3 3 4 4 7 3 3 4 6 9 3 3 4 8 3 3 3 4 30 33 3 Check Check Check Check 35
More information80 X 1, X 2,, X n ( λ ) λ P(X = x) = f (x; λ) = λx e λ, x = 0, 1, 2, x! l(λ) = n f (x i ; λ) = i=1 i=1 n λ x i e λ i=1 x i! = λ n i=1 x i e nλ n i=1 x
80 X 1, X 2,, X n ( λ ) λ P(X = x) = f (x; λ) = λx e λ, x = 0, 1, 2, x! l(λ) = n f (x i ; λ) = n λ x i e λ x i! = λ n x i e nλ n x i! n n log l(λ) = log(λ) x i nλ log( x i!) log l(λ) λ = 1 λ n x i n =
More information(1) (2) 27 7 15 (1) (2), E-mail: bessho@econ.keio.ac.jp 1 2 1.1......................................... 2 1.2............................... 2 1.3............................... 3 1.4............................
More information10 2000 11 11 48 ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) CU-SeeMe NetMeeting Phoenix mini SeeMe Integrated Services Digital Network 64kbps 16kbps 128kbps 384kbps
More informationZE_Œ{‘‚‡Ì„©Łû
87 5 7 1 2002 8 28 1 2 29 e r w 7 5 q Excel 20022000 2000 2002 2000 2002 STEP UP Check 2000 CONTENTS Excel 20022000 2000 5 1 15 1 1 2 5 7 18 ce 20 22 2 2 28 2002 0 2 8 9 10 11 12 1 1 1 2 8 0 2 2002 8 50
More information1 2 3 1 34060120 1,00040 2,000 1 5 10 50 2014B 305,000140 285 5 6 9 1,838 50 922 78 5025 50 10 1 2
0120-563-506 / 9001800 9001700 123113 0120-860-777 163-8626 6-13-1 Tel.03-6742-3111 http://www.himawari-life.co.jp 1 2 3 1 34060120 1,00040 2,000 1 5 10 50 2014B 305,000140 285 5 6 9 1,838 50 922 78 5025
More informationGray [6] cross tabulation CUBE, ROLL UP Johnson [7] pivoting SQL 3. SuperSQL SuperSQL SuperSQL SQL [1] [2] SQL SELECT GENERATE <media> <TFE> GENER- AT
DEIM Forum 2017 E3-1 SuperSQL 223 8522 3 14 1 E-mail: {tabata,goto}@db.ics.keio.ac.jp, toyama@ics.keio.ac.jp,,,, SuperSQL SuperSQL, SuperSQL. SuperSQL 1. SuperSQL, Cross table, SQL,. 1 1 2 4. 1 SuperSQL
More information1 J 2 tasu =: + (Tacit definition) (Explicit definition) 1.1 (&) x u&v y Fork Bond & Bond(&) 0&{ u u v v v y x y 1&{ ( p) ( q) x v&
1 J SHIMURA Masato jcd02773@nifty.ne.jp 2008 12 8 1 J 1 2 J 4 3 5 4 8 5 /de Morgan law 11 6 16 7 19 8 Reference 21 A 21 J 5 1 J J Atom ) APL J 1 J 2 tasu =: + (Tacit definition) (Explicit definition) 1.1
More informationelemmay09.pub
Elementary Activity Bank Activity Bank Activity Bank Activity Bank Activity Bank Activity Bank Activity Bank Activity Bank Activity Bank Activity Bank Activity Bank Activity Bank Number Challenge Time:
More information1. A0 A B A0 A : A1,...,A5 B : B1,...,B
1. A0 A B A0 A : A1,...,A5 B : B1,...,B12 2. 3. 4. 5. A0 A B f : A B 4 (i) f (ii) f (iii) C 2 g, h: C A f g = f h g = h (iv) C 2 g, h: B C g f = h f g = h 4 (1) (i) (iii) (2) (iii) (i) (3) (ii) (iv) (4)
More information-2-
-1- -2- -3- -4- -5- -6- -7- -8- 10-9- -10-1 2 -11-1 1-12- -13- -14- Plan Do Check Action Check Action 1 -15- -16- -17- -18- -19- -20- -21- -22- 10 2 9 3 9 2 1 10 2 9 3 6 4 1 6 6 10 2 10 2 11 1 8 1 8 4
More information平成20年度内部評価実施結果報告書《本編》
10 11 12 13 14 15 16 17 Plan Do Check Action 1 2 3 4 146 13 20 43 44 45 62 104 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47
More informationuntitled
1 1 2 3 2 1 ( 0) 2000 00 3 4 Check Action Do Plan 5 6 14001 5000 5000 1000 1000 7 8 9 10 2004 0.1 0.1 0.0 0.0 0.0 15.3 483.5 0.4 11 12 13 14 http://kankyou.pref.shizuoka.jp/seikan/seikanindex.htm 15 16
More information技術流出防止指針公表用.PDF
15 3 1 4 .. 2 2.. 4. 6.10 10.14.16.19.24.26.28 1 2 1 2002 7 3 2002 3 4 2 3 5 4 4 6 7 8 5 5 9 plan (do) (check) (act) 1) 2) 3) 4) 5) 6) 7) 10 11 12 13 14 15 16 17 18 6 6 19 / / 20 21 22 7 23 8 24 25 26
More informationこんにちは由美子です
Sample size power calculation Sample Size Estimation AZTPIAIDS AIDSAZT AIDSPI AIDSRNA AZTPr (S A ) = π A, PIPr (S B ) = π B AIDS (sampling)(inference) π A, π B π A - π B = 0.20 PI 20 20AZT, PI 10 6 8 HIV-RNA
More information3 1-1 4
2 0 0 4 P CKK 1 2 3 1-1 4 1-2 5 1-3 6 1-4 PFI 7 1-5 8 1-6 9 1-7 10 2-1PFI 11 12 13 14 2-3 15 2-4 16 2-5. ( ) 17 2-6 ( ) () 16123 18 2-6 ( ) () 16123 19 2-7 20 2-8 21 2-9 ( ) 22 23 3-1 PFI 24 3-2 3-3 25
More information1 bmp gif,png,jpg bmp gif,png jpg BPG 2014 jpg *3 RAW TIFF RAW CCD CMOS R,G,B TIFF net *4 1.1 JPEG HP JPEG 3 1 4, 1 8, 1 16 JPEG SD jpeg JPEG RGB YCrC
Viewmat SHIMURA Masato 2015 6 12 viewnmat viewmat QT J8x 400 RGB CMYK *1 *2 RGB CMYK *1 CMYK,, *2 1 1 bmp gif,png,jpg bmp gif,png jpg BPG 2014 jpg *3 RAW TIFF RAW CCD CMOS R,G,B TIFF net *4 1.1 JPEG HP
More informationAtCoder Regular Contest 073 Editorial Kohei Morita(yosupo) A: Shiritori if python3 a, b, c = input().split() if a[len(a)-1] == b[0] and b[len(
AtCoder Regular Contest 073 Editorial Kohei Morita(yosupo) 29 4 29 A: Shiritori if python3 a, b, c = input().split() if a[len(a)-1] == b[0] and b[len(b)-1] == c[0]: print( YES ) else: print( NO ) 1 B:
More information6.1 OOP Multi Sub a
/ WIN [ ] Masato SHIMURA JCD2773@nifty.ne.jp Last update 25 4 23 1 J 2 1.1....................................... 2 2 D 2 2.1 numeric trig................................... 6 3 6 3.1 X;Y....................................
More information第29回日中石炭関係総合会議
1 2 3 4 5 6 闞 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 闞 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69
More informationEVALUATION OF NOCTURNAL PENILE TUMESCENCE (NPT) IN THE DIFFERENTIAL DIAGNOSIS OF IMPOTENCE Masaharu Aoki, Yoshiaki Kumamoto, Kazutomi Mohri and Kazunori Ohno Department of Urology, Sapporo Medical College
More information最小2乗法
2 2012 4 ( ) 2 2012 4 1 / 42 X Y Y = f (X ; Z) linear regression model X Y slope X 1 Y (X, Y ) 1 (X, Y ) ( ) 2 2012 4 2 / 42 1 β = β = β (4.2) = β 0 + β (4.3) ( ) 2 2012 4 3 / 42 = β 0 + β + (4.4) ( )
More informationはじめに
IT 1 NPO (IPEC) 55.7 29.5 Web TOEIC Nice to meet you. How are you doing? 1 type (2002 5 )66 15 1 IT Java (IZUMA, Tsuyuki) James Robinson James James James Oh, YOU are Tsuyuki! Finally, huh? What's going
More information206“ƒŁ\”ƒ-fl_“H„¤‰ZŁñ
51 206 51 63 2007 GIS 51 1 60 52 2 60 1 52 3 61 2 52 61 3 58 61 4 58 Summary 63 60 20022005 2004 40km 7,10025 2002 2005 19 3 19 GIS 2005GIS 2006 2002 2004 GIS 52 2062007 1 2004 GIS Fig.1 GIS ESRIArcView
More informationC言語によるアルゴリズムとデータ構造
Algorithms and Data Structures in C 4 algorithm List - /* */ #include List - int main(void) { int a, b, c; int max; /* */ Ÿ 3Ÿ 2Ÿ 3 printf(""); printf(""); printf(""); scanf("%d", &a); scanf("%d",
More informationAR(1) y t = φy t 1 + ɛ t, ɛ t N(0, σ 2 ) 1. Mean of y t given y t 1, y t 2, E(y t y t 1, y t 2, ) = φy t 1 2. Variance of y t given y t 1, y t
87 6.1 AR(1) y t = φy t 1 + ɛ t, ɛ t N(0, σ 2 ) 1. Mean of y t given y t 1, y t 2, E(y t y t 1, y t 2, ) = φy t 1 2. Variance of y t given y t 1, y t 2, V(y t y t 1, y t 2, ) = σ 2 3. Thus, y t y t 1,
More information!!! 10 1 110 88 7 9 91 79 81 82 87 6 5 90 83 75 77 12 80 8 11 89 84 76 78 85 86 4 2 32 64 10 44 13 17 94 34 33 107 96 14 105 16 97 99 100 106 103 98 63 at 29, 66 at 58 12 16 17 25 56
More informationuntitled
146,650 168,577 116,665 122,915 22,420 23,100 7,564 22,562 140,317 166,252 133,581 158,677 186 376 204 257 5,594 6,167 750 775 6,333 2,325 298 88 5,358 756 1,273 1,657 - - 23,905 23,923 1,749 489 1,309
More information1 # include < stdio.h> 2 # include < string.h> 3 4 int main (){ 5 char str [222]; 6 scanf ("%s", str ); 7 int n= strlen ( str ); 8 for ( int i=n -2; i
ABC066 / ARC077 writer: nuip 2017 7 1 For International Readers: English editorial starts from page 8. A : ringring a + b b + c a + c a, b, c a + b + c 1 # include < stdio.h> 2 3 int main (){ 4 int a,
More information名称未設定-4
(I and Asphalt Emulsion) (The Boy Met the Road Pavement in a Rough Gravel Road) (Growth Factor of Young-Engineer) (My Interest in the Pavement) (Expressway and Pavement -Feeling as a Researcher-) Act
More informationuntitled
CAPEC, 2009 6 16 June 16, 2009 Page 1 CAPEC EMS 1. EMS USA EU 2. EMS 3. EMS 4. EMS 5. CAPEC 6. EMS June 16, 2009 Page 2 EMS EC 3 EMS EMS EMS EMS CAPEC EMS CAPEC EMS EMS June 16, 2009 Page 3 EU EU EC 1997/67/EC
More information44 2012 2013 3 35 48 法人化後の国立大学の収入変動 37 法人化後の国立大学の収入変動 2009 2005 2010 2012 2012 2008 2009a 2010 16 18 17 20 2 4 2012 38 44 2012 17 22 (1) (2) 2012 5 GP COE 30 WPI 1 2012 17 22 16 17 22 17 17 19 2012 2012
More information2 The Bulletin of Meiji University of Integrative Medicine 3, Yamashita 10 11
1-122013 1 2 1 2 20 2,000 2009 12 1 2 1,362 68.1 2009 1 1 9.5 1 2.2 3.6 0.82.9 1.0 0.2 2 4 3 1 2 4 3 Key words acupuncture and moxibustion Treatment with acupuncture, moxibustion and Anma-Massage-Shiatsu
More informationkubostat2018d p.2 :? bod size x and fertilization f change seed number? : a statistical model for this example? i response variable seed number : { i
kubostat2018d p.1 I 2018 (d) model selection and kubo@ees.hokudai.ac.jp http://goo.gl/76c4i 2018 06 25 : 2018 06 21 17:45 1 2 3 4 :? AIC : deviance model selection misunderstanding kubostat2018d (http://goo.gl/76c4i)
More information: Shift-Return evaluate 2.3 Sage? Shift-Return abs 2 abs? 2: abs 3: fac
Bulletin of JSSAC(2012) Vol. 18, No. 2, pp. 161-171 : Sage 1 Sage Mathematica Sage (William Stein) 2005 2 2006 2 UCSD Sage Days 1 Sage 1.0 4.7.2 1) Sage Maxima, R 2 Sage Firefox Internet Explorer Sage
More information10 11 12 33.4 1 open / window / I / shall / the? 79.3 2 something / want / drink / I / to. 43.5 3 the way / you / tell / the library / would / to / me
-1- 10 11 12 33.4 1 open / window / I / shall / the? 79.3 2 something / want / drink / I / to. 43.5 3 the way / you / tell / the library / would / to / me? 28.7 4 Miyazaki / you / will / in / long / stay
More information情報科学概論 第1回資料
1. Excel (C) Hiroshi Pen Fujimori 1 2. (Excel) 2.1 Excel : 2.2Excel Excel (C) Hiroshi Pen Fujimori 2 256 (IV) :C (C 65536 B4 :2 (2 A3 Excel (C) Hiroshi Pen Fujimori 3 Tips: (1) B3 (2) (*1) (3) (4)Word
More informationHow to read the marks and remarks used in this parts book. Section 1 : Explanation of Code Use In MRK Column OO : Interchangeable between the new part
Reservdelskatalog MIKASA MVB-85 rullvibrator EPOX Maskin AB Postadress Besöksadress Telefon Fax e-post Hemsida Version Box 6060 Landsvägen 1 08-754 71 60 08-754 81 00 info@epox.se www.epox.se 1,0 192 06
More information2013 Future University Hakodate 2013 System Information Science Practice Group Report biblive : Project Name biblive : Recording and sharing experienc
2013 Future University Hakodate 2013 System Information Science Practice Group Report biblive : Project Name B biblive stream Group Name GroupB biblive stream /Project No. 12-B /Project Leader 1011063
More informationt 2 2 t 2 t F ( ) p- 2 2 F 2 G F ( ) 2 2 F 2 G F ( ) 2 2 2
1 2 2 0 1 2 2 2 2 2 2 2 2.1 2 2 F={f ij }, G {g ij } t f ij t g ij = 1 f ij < t g ij = 0 t p- p S 0 S p = S 0 /S t p 2 t 1 t 2 2 t 2 t 2 2 3 3 1 2 F ( ) p- 2 2 F 2 G 3 2 2 F ( ) 2 2 F 2 G 3 3 2 F ( ) 2
More informationHow to read the marks and remarks used in this parts book. Section 1 : Explanation of Code Use In MRK Column OO : Interchangeable between the new part
Reservdelskatalog MIKASA MT65H vibratorstamp EPOX Maskin AB Postadress Besöksadress Telefon Fax e-post Hemsida Version Box 6060 Landsvägen 1 08-754 71 60 08-754 81 00 info@epox.se www.epox.se 1,0 192 06
More informationHow to read the marks and remarks used in this parts book. Section 1 : Explanation of Code Use In MRK Column OO : Interchangeable between the new part
Reservdelskatalog MIKASA MVC-50 vibratorplatta EPOX Maskin AB Postadress Besöksadress Telefon Fax e-post Hemsida Version Box 6060 Landsvägen 1 08-754 71 60 08-754 81 00 info@epox.se www.epox.se 1,0 192
More informationNumerical Analysis II, Exam End Term Spring 2017
H. Ammari W. Wu S. Yu Spring Term 2017 Numerical Analysis II ETH Zürich D-MATH End Term Spring 2017 Problem 1 Consider dx = f(t, x), t [0, T ] dt x(0) = x 0 R [28 Marks] with f C subject to the Lipschitz
More information2 Excel =sum( ) =average( ) B15:D20 : $E$26 E26 $ =A26*$E$26 $ $E26 E$26 E$26 $G34 $ E26 F4
1234567 0.1234567 = 2 3 =2+3 =2-3 =2*3 =2/3 =2^3 1:^, 2:*/, 3:+- () =2+3*4 =(2+3)*4 =3*2^2 =(3*2)^2 =(3+6)^0.5 A12 =A12+B12 ( ) ( )0.4 ( 100)0.9 % 1 2 Excel =sum( ) =average( ) B15:D20 : $E$26 E26 $ =A26*$E$26
More information02[021-046]小山・池田(責)岩.indd
Developing a Japanese Enryo-Sasshi Communication Scale: Revising a Trial Version of a Scale Based on Results of a Pilot Survey KOYAMA Shinji and IKEDA Yutaka Toward exploring Japanese Enryo-Sasshi communication
More information161 J 1 J 1997 FC 1998 J J J J J2 J1 J2 J1 J2 J1 J J1 J1 J J 2011 FIFA 2012 J 40 56
J1 J1 リーグチーム組織に関する考察 松原悟 Abstract J League began in 1993 by 10 teams. J League increased them by 40 teams in 2012. The numerical increase of such a team is a result of the activity of Football Association
More informationHow to read the marks and remarks used in this parts book. Section 1 : Explanation of Code Use In MRK Column OO : Interchangeable between the new part
Reservdelskatalog MIKASA MCD-L14 asfalt- och betongsåg EPOX Maskin AB Postadress Besöksadress Telefon Fax e-post Hemsida Version Box 6060 Landsvägen 1 08-754 71 60 08-754 81 00 info@epox.se www.epox.se
More information2012専門分科会_new_4.pptx
d dt L L = 0 q i q i d dt L L = 0 r i i r i r r + Δr Δr δl = 0 dl dt = d dt i L L q i q i + q i i q i = q d L L i + q i i dt q i i q i = i L L q i L = 0, H = q q i L = E i q i i d dt L q q i i L = L(q
More information磐田市水道事業ビジョン
20162025 I w a t a C i t y W a t e r w o r k s V i s i o n C o n t e n t s 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2049 (H21) (H22) (H23) (H24) (H25) (H26)
More information