JMSL 3.0 FC_日_ .doc
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1 V E R S I O N 3. 0 JMSL Numerical Library Function Catalog
2 JMSL Numerical Library Function Catalog Java 4 7 IMSLC C# Fortran 8 com.imsl Package 9 com.imsl.math Package com.imsl.stat Package
3 JMSL Numerical Library Function Catalog com.imsl.datamining.neural Package 21 com.imsl.finance Package 23 com.imsl.chart Package 26 com.imsl.chart.xml Package 29 com.imsl.io Package 29 3
4 Java TM JMSL TM 4
5 5 30 IMSL JMSL Numerical Library Function Catalog
6 JMSL Numerical Library Function Catalog Swing IMSL 6
7 7 JMSL Numerical Library Function Catalog
8 8 JMSL Numerical Library Function Catalog
9 com.imsl com.imsl Messages Version Warning WarningObject 9
10 com.imsl.math com.imsl.math Complex Matrix ComplexMatrix LU ComplexLU Cholesky QR SVD Ax = b Ax = b Ax = b 2 Ax = b A A = USVT Eigen SymEigen A A 10
11 com.imsl.math Spline CsInterpolate CsAkima CsPeriodic CsShape CsSmooth CsSmoothC2 Bspline BsInterpolate BsLeastSquares RedialBases Spline Akima Spline Spline Spline Spline Spline B B- Bspline 2 Bspline 2 Quadrature HypercubeQuadrature OdeRungeKutta Runge-Kutta-Verner 11
12 com.imsl.math FFT ComplexFFT ZeroPolynomial ZeroFunction ZeroSystem Aberth Müller Powell n f (x) = 0 MinUncon MinUnconMultiVar NonlinLeastSquares LinearProgramming QuadraticProgramming MinConGenLin BoundedLeastSquares MinConNLP f(x) n f(x) Levenberg-Marquardt 2 Levenberg-Marquardt 2 Sfun -beta -betaincomplete 12
13 com.imsl.math - cot - erf - erfc - erfcinverse - erfinverse - fact - gamma - log10 - logbeta - loggamma - poch Pochhammer - sign Bessel Bessel - I Bessel - I Bessel - J Bessel - J Bessel - K Bessel - K Bessel - scaledk Bessel - Y 2 Bessel 13
14 com.imsl.math Jmath IEEE java.long.math Pure Java 2 IEEE754 Pure Java Hyperbolic Pure Java - acosh - asinh - atanh - cosh - expm1 exp(x)-1 - log1p loy(1+x)-1 - sinh - tanh Physical EpsilonAlgorithm PrintMatrix PrintMatrixFormat PrintMatrix 14
15 com.imsl.stat com.imsl.stat ANOVA Summary - ConfidenceMean - ConfidenceVariance - Kurtosis - Maximum - Mean - Median - Minimum - Mode - SampleStandardDeviation - SampleVariance - Skewness - StandardDeviation - Variance 15
16 com.imsl.stat NormOneSample NormTwoSample TableOneWay TableTwoWay TableMultiWay Sort Ranks 2 2 Covariances LinearRegression NonlinearRegression UserBasisRegression RegressionBasis SelectionRegresstion StepwiseRegression 2 2 UserBasisRegression ANOVA ANOVAFactorial MultipleComparisons Student-Newman-Keuls 16
17 com.imsl.stat ContigencyTable CategoricalGenLinModel 2 Poisson SignTest WilcoxonRankSum Wilcoxon ChiSquaredTest NormalityTest 2 AutoCorrelation Cross Correlation MultiCrossCorrelationn ARMA Difference GARCH KalmanFilter 2 Student-Newman-Keuls ARMA ARMA GARCH(p,q) Kalman ClusterKMeans Dissimilarities K-means ( ) 17
18 com.imsl.stat ClusterHierachical Factor Analysis DiscriminantAnalysis 2 Cdf - Beta - Binomial 2 - BinomialProb 2 - Chi 2 - F F - Gamma - Hypergeometric - HypergeometricProb - InverseBeta - InverseChi 2 - InverseF F - InverseGamma - InverseNomal (Gaussian) - InversetsT Student t - Normal (Gaussian) - Poisson Poisson - PoissonProb Poisson 18
19 com.imsl.stat StudentsT Weibull InverseCdf Student t Weibull FaureSequence Random Faure - NextBeta - NextBinomial - NextCauchy Cauchy - NextChiSquared - NextExponential - NextExponentialMix - NextGamma - NextGeometric - NextHypergeometric - NextLogarithmic - NextLogNormal - NextMultivariateNormal - NextNegativeBinomial - NextNormal CDF - NextNormalAR 19
20 com.imsl.stat - NextPoisson Poisson - NextStudentsT Student t - NextTriangular 0,1 - NextVonMises VonMises - NextWeibull Weibull - SetMultiplier - SetSeed - Skip 20
21 com.imsl.detamining.neural com.imsl.detamining.neural Network FeedForwardNetwork Layer InputLayer HiddenLayer OutputLayer Node InputNode Perceptron OutputPerceptron Activation Link Trainer QuasiNewtonTrainer LeastSquaresTrainer Epoch Trainer 2 Levenberg-Marqard
22 com.imsl.detamining.neural ScaleFilter UnsupervisedNominalFilter UnsupervisedOrdinalFilter TimeSeriesFilter TimeSeriesClassFilter 2 22
23 com.imsl.finance com.imsl.finance DayCountBasis Bond - Accrint - Accrintm - Amordegrc - Amorlinc - Convexity - Coupdaybs - Coupdays 23
24 com.imsl.finance - Coupdaysnc - Coupncd - Coupnum - Couppcd - Disc - Duration - Intrate - Mduration - Price $100 - Pricedisc Pricemat Priceyield - Received - Tbilleq (TB) - Tbillprice (TB)100 - Tbillyield (TB) - Yearfrac - Yield. - Yielddisc - Yieldmat Finance - Cumipmt - Cumprinc 24
25 com.imsl.finance - Db - Ddb - Dollarde - Dollarfr - Effect - Fv - Fvschedule - Ipmt - Irr - Mirr - Nominal - Nper - Npv - Pmt - Ppmt - Pv - Rate - Sln - Syd - Vdb - Xirr - Xnpv 25
26 com.imsl.chart com.imsl.chart High-Low-Close-Open JMSL Axis Axis1D AxisLabel AxisLine AxisR AxisRLabel AxisRLine Axis X Y R 26
27 27 AxisRMajorTick AxisTheta AxisTitle AxisUnit AxisXY x-y Background Bar BarItem BarSet BoxPlot Candlestick CandlestickItem Chart ChartNode ChartServlet ChartSpline ChartFunction ChartTitle Contour Data Draw DrawMap HTML DrawPick ErrorBar com.imsl.chart
28 com.imsl.chart FillPaint Grid GridPolar HighLowClose JFrameChart JPanelChart JspBean Legend MajorTick MinorTick PickEvent Pie PieSlice Polar SplineData Text ToolTip Transform Paint Hi-lo-close JframeChart JFrame Swing JPanel Java Spline Title ToolTip TransformDate Heatmap RGB ColorMap 28
29 com.imsl.chart.xml ChartXML XML com.imsl.io AbstractFlatFile ResultSet FlatFile ResultSet Tokenizer 29
V E R S I O N C# Numerical Library Function Catalog
V E R S I O N 4.0. 2 C# Numerical Library Function Catalog 目次 1 IMSL C# ライブラリ4.02 概要 2 Imsl.Math Package 5 基本関数 5 線形代数 5 固有値解析 5 補間と近似 5 積分 5 微分方程式 6 変換 6 非線形方程式 6 最適化 6 特殊関数 6 その他 7 印刷関数 7 Imsl.Stat Package
imslfunction1.qxd
VERSION 5.5 C Numerical Library Function Catalog IMSL TM C Numerical Library Function Catalog IMSL C 3 6 7 IMSL Java TM Fortran 8 IMSL C Math / Library 9 10 10 12 13 13 14 15 15 21 22 22 IMSL C / Stat
fortranfunction2.qxd
Fortran Numerical Library Function Catalog IMSL TM Fortran Numerical Library Function Catalog IMSL Fortran 4 8 9 10 IMSL Java TM C 12 IMSL Math / Library 13 13 21 23 27 28 29 31 32 34 40 41 IMSL Math /
CNL社内製本用.PDF
VERSION 6.0 C Numerical Library Function Catalog IMSL TM C IMSL C Math / Library IMSL C / Stat / Library 1 IMSL TM C IMSL C IMSL C IMSL C IMSL C IMSL C IMSL C C IMSL C UNIX/Linux Windows 3 IMSL C IMSL
Numbers '08 ユーザーズガイド
Numbers 08 KAppleInc. 2008AppleInc.Allrightsreserved. Apple Apple AppleInc. Apple Apple Apple 1InfiniteLoop Cupertino,CA95014-2084 U.S.A. www.apple.com 163-1480 3 20 2 www.apple.com/jp AppleApple AppleWorksColorSynciMovie
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KINGSOFT Office 対応関数一覧
KINGSOFT Office 対 応 関 数 一 覧 関 数 属 性 関 数 名 内 容 キングソ MSバー フト 対 応 ジョン 互 換 性 関 数 BETADIST 関 数 β 分 布 の 累 積 分 布 関 数 の 値 2010 互 換 性 関 数 BETAINV 関 数 β 分 布 の 分 布 関 数 の 逆 関 数 の 値 2010 互 換 性 関 数 BINOMDIST 関 数 二 項
Isogai, T., Building a dynamic correlation network for fat-tailed financial asset returns, Applied Network Science (7):-24, 206,
H28. (TMU) 206 8 29 / 34 2 3 4 5 6 Isogai, T., Building a dynamic correlation network for fat-tailed financial asset returns, Applied Network Science (7):-24, 206, http://link.springer.com/article/0.007/s409-06-0008-x
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2012 11 01 k2 (2012-10-26 16:35 ) 1 6 2 (2012 11 01 k2) (GLM) kubo@ees.hokudai.ac.jp web http://goo.gl/wijx2 web http://goo.gl/ufq2 1 : 2 2 4 3 7 4 9 5 : 11 5.1................... 13 6 14 6.1......................
本書の読み方 本書では すべての関数の機能や引数の意味などを解説しています 目的の関数は 2 つのインデックスからすぐに見つけられます また 使用例 や ポイント がある関数では 具体的な使い方や+αの知識を身に付けられます 各要素の詳しい内容は以下を参照してください 分類 関数の機能の大まかな分類
本書の読み方 本書では すべての関数の機能や引数の意味などを解説しています 目的の関数は 2 つのインデックスからすぐに見つけられます また 使用例 や ポイント がある関数では 具体的な使い方や+αの知識を身に付けられます 各要素の詳しい内容は以下を参照してください 分類 関数の機能の大まかな分類を表しています 対応バージョン 関数が対応する Excel のバージョンを表しています 機能 関数で行える計算や処理を表しています
関数対応表(MS2016KS2016).xls
関数属性 関数名 内容 数学 / 三角関数 ABS 関数 数値の絶対値を返します 財務関数 ACCRINT 関数 定期的に利息が支払われる証券の未収利息額を返します 財務関数 ACCRINTM 関数 満期日に利息が支払われる証券の未収利息額を返します 数学 / 三角関数 ACOS 関数 数値のアークコサインを返します 数学 / 三角関数 ACOSH 関数 数値の双曲線逆余弦 ( ハイパーボリックコサインの逆関数
講義のーと : データ解析のための統計モデリング. 第２回
Title 講義のーと : データ解析のための統計モデリング Author(s) 久保, 拓弥 Issue Date 2008 Doc URL http://hdl.handle.net/2115/49477 Type learningobject Note この講義資料は, 著者のホームページ http://hosho.ees.hokudai.ac.jp/~kub ードできます Note(URL)http://hosho.ees.hokudai.ac.jp/~kubo/ce/EesLecture20
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講義のーと : データ解析のための統計モデリング. 第３回
Title 講義のーと : データ解析のための統計モデリング Author(s) 久保, 拓弥 Issue Date 2008 Doc URL http://hdl.handle.net/2115/49477 Type learningobject Note この講義資料は, 著者のホームページ http://hosho.ees.hokudai.ac.jp/~kub ードできます Note(URL)http://hosho.ees.hokudai.ac.jp/~kubo/ce/EesLecture20
0104.pages
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