Scripting Guide - SAS

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598 JSL Syntax Reference Appendix A Discrete Probability Functions n number of trials k number of successes See Also The section on probability functions in the Using JMP. Binomial Quantile(p, n, cumprob) Description The quantile function of binomial distribution. Returns The smallest integer quantile for which the cumulative probability of the Binomial(p, n) distribution is larger than or equal to cumprob. Arguments p probability of success for each trial n number of trials cumprob cumulative probability Gamma Poisson Distribution(k, lambda, sigma) Description Returns the probability that a gamma-Poisson distributed random variable is less than or equal to k. Arguments k The count of interest. lambda The mean parameter. sigma The overdispersion parameter. Gamma Poisson Probability(k, lambda, sigma) Description Returns the probability that a gamma-Poisson distributed random variable is equal to k. Arguments k The count of interest. lambda The mean parameter. sigma The overdispersion parameter. Gamma Poisson Quantile(lambda, sigma, cumprob) Description Returns the smallest integer quantile for which the cumulative probability of the Gamma Poisson(lambda, sigma) distribution is larger than or equal to cumprob.
Appendix A JSL Syntax Reference 599 Discrete Probability Functions Hypergeometric Distribution(N, K, n, x, ) Description Returns the cumulative distribution function at x for the hypergeometric distribution with population size N, K items in the category of interest, sample size n, count of interest x, and optional odds ratio r. Hypergeometric Probability(pop, k, n, x, ) Description Returns the probability that a hypergeometrically distributed random variable is equal to x. Arguments pop Population size. k The Number of items in the category of interest. n Sample size. x Count of interest. r Optional odds ratio. Neg Binomial Distribution(p, n, k) Description Returns the probability that a negative binomially distributed random variable is less than or equal to k, where the probability of success is p and the number of successes is n. Neg Binomial Probability(p, n, k) Description Returns the probability that a negative binomially distributed random variable is equal to k, where the probability of success is p and the number of successes is n. Poisson Distribution(lambda, k) Description Returns the cumulative distribution function at k for the Poisson distribution with mean lambda. Poisson Probability(lambda, k) Description Returns the probability that a Poisson distributed random variable with mean lambda is equal to k. Poisson Quantile(lambda, cumprob) Description Returns the smallest integer quantile for which the cumulative probability of the Poisson(lambda) distribution is larger than or equal to cumprob.
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Version 10 Scripting Guide “The r
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INDIRECT OR CONSEQUENTIAL DAMAGES O
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6 Capturing a Script for a Data Tab
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8 Repeat . . . . . . . . . . . . .
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10 Getting a Data Table Object . .
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12 Build Your Own Displays from Scr
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14 Using the mouse . . . . . . . .
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16 B Discrete Probability Functions
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Chapter 1 Learn about JMP Documenta
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Chapter 1 Learn about JMP 21 Book C
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Chapter 1 Learn about JMP 23 Book C
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Chapter 1 Learn about JMP 25 Additi
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Chapter 1 Learn about JMP 27 Additi
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Chapter 2 Introduction Welcome to t
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Chapter 2 Introduction 31 What JSL
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Chapter 2 Introduction 33 Terminolo
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Chapter 2 Introduction 35 Terminolo
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Chapter 3 Getting Started Let JMP W
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Chapter 3 Getting Started 39 Captur
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Chapter 3 Getting Started 41 Captur
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Chapter 3 Getting Started 43 Gluing
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Chapter 3 Getting Started 45 Gluing
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Chapter 4 Scripting Tools Using the
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Chapter 4 Scripting Tools 49 Using
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Chapter 4 Scripting Tools 55 Workin
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Chapter 4 Scripting Tools 57 Debug
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Chapter 5 JSL Building Blocks Learn
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Chapter 5 JSL Building Blocks 71 JS
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Chapter 5 JSL Building Blocks 73 JS
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Chapter 5 JSL Building Blocks 95 In
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Chapter 5 JSL Building Blocks 97 Na
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Chapter 6 Types of Data Working wit
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Chapter 6 Types of Data 105 Numbers
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Chapter 6 Types of Data 107 Path Va
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Chapter 6 Types of Data 109 Date-Ti
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Chapter 6 Types of Data 119 Currenc
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Chapter 6 Types of Data 121 Hexadec
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Chapter 6 Types of Data 123 Work wi
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Chapter 6 Types of Data 125 Use Pat
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Chapter 6 Types of Data 127 Use Pat
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Chapter 7 Data Structures Working w
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Chapter 7 Data Structures 131 Lists
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Chapter 7 Data Structures 137 Matri
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Chapter 7 Data Structures 169 Assoc
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Chapter 8 Programming Methods Compl
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Chapter 8 Programming Methods 231 F
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Chapter 9 Data Tables Create, Open,
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Chapter 9 Data Tables 235 Data Tabl
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Chapter 9 Data Tables 243 Messages
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Chapter 9 Data Tables 275 Manipulat
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Chapter 9 Data Tables 287 Row State
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Chapter 9 Data Tables 303 Calculati
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Chapter 9 Data Tables 305 Calculati
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Chapter 10 Scripting Platforms Crea
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Chapter 10 Scripting Platforms 309
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Chapter 11 Display Trees Create and
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Chapter 11 Display Trees 331 Manipu
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Chapter 11 Display Trees 343 How to
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Chapter 11 Display Trees 345 Constr
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Chapter 11 Display Trees 373 Modal
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Chapter 11 Display Trees 383 Syntax
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Chapter 12 Scripting Graphs Create
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Chapter 12 Scripting Graphs 393 Add
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Chapter 13 Three-Dimensional Scenes
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Chapter 14 Extending JMP 469 Real-T
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Chapter 14 Extending JMP 475 Dynami
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Chapter 14 Extending JMP 477 Using
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Chapter 14 Extending JMP 479 Databa
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Chapter 14 Extending JMP 481 Workin
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Chapter 14 Extending JMP 495 OLE Au
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Chapter 15 Creating and Sharing App
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Chapter 16 Common Tasks Getting Sta
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Chapter 16 Common Tasks 533 Convert
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Chapter 16 Common Tasks 535 Format
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Chapter 16 Common Tasks 537 Create
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Chapter 16 Common Tasks 539 Extract
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Index JSL Syntax Reference Symbols
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Page 555 and 556: Appendix A JSL Syntax Reference Sum
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Appendix B Messages 741 Associative
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Appendix B Messages 743 Data Tables
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Appendix B Messages 763 Display Box
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Appendix B Messages 781 R Integrati
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Appendix B Messages 783 SAS Integra
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Appendix B Messages 801 Sockets For
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Appendix C Compatibility Notes Chan
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Appendix D Glossary Terms, Concepts
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Appendix D Glossary 813 ODBC databa
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Index JMP Scripting Guide Symbols `
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Index 817 property parameters 284 c
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Index 819 Disable 465 Disk 448 Disp
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Index 821 HLine 405 HList 377, 380
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Index 823 objects 240 platform 310
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Index 825 Point Size 443 POINTS 440
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Index 827 Show Properties 243, 276,
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