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Alphabetical List of Features

This list is a guide to JMP features. Where appropriate, the feature is followed by the name of the platform where the feature is found. Newest features are bold.

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A

  • ABCD design—screening design for mixtures, DOE, Mixture Design
  • Accelerated failure—parametric survival models, Fit Model > Parametric Survival
  • actuarial life table templates included (see templates)
  • added-variable plot (see leverage plot)
  • adjusted means (see least squares means)
  • A-efficiency (D-optimal designs), DOE, Custom Design
  • AIAG labels—variability chart option, Variability/Gage Chart
  • AIC, Akaike’s ‘A’ Information Criterion, Fit Model Stepwise
  • Alias matrix—shows bias from two-factor interactions not in the model, Custom Design DOE
  • aliasing structure table—shows confounding patterns
  • all possible regressions—Fit Model Stepwise
  • alpha level specification (optional in many platforms)
  • analysis of covariance—same slopes, Fit Model SLS
  • analysis of covariance—separate slopes, Fit Model SLS
  • analysis of loglikelihood, likelihood ratio—Chi-square test of how well categorical model fits, Fit Y by X categorical, Fit Model Nominal or Ordinal Logistic
  • analysis of variance (general)—profile, contrasts, custom tests, crossed, nested, polynomial, surface and random effects, LSMeans, student’s t and Tukey tests for multiway ANOVA, mixed models (with no assignable covariance structure) using REML estimation, Fit Model
  • analysis of variance (one-way)—F test (or t-test if there are only two levels), Fit Y by X oneway
  • analysis of variance ( non-parametric)—Wilcoxon, Median and Van der Waerden tests, Fit Y by X oneway
  • animation of statistical graphics—JSL application (see scripting language, some scripts built in
  • ANOVA (see analysis of variance), Fit Y by X, Fit Model
  • ANCOVA (see analysis of covariance), Fit Model
  • AR coefficients plot and values—diagnostic for time series modeling, Modeling > Time Series
  • ARIMA and seasonal ARIMA forecasting (see time series modeling and forecasting), Modeling > Time Series
  • attribute charts—p, np, c, and u control charts, Control Chart
  • attribute gage charts
  • augmented designs—replicate, add center or axial points, foldover designs, DOE, Augment Design
  • autocorrelation—Durbin Watson test for autocorrelation, Fit Model SLS
  • autocorrelation plots and values—diagnostic for time series modeling, Modeling > Time Series
  • auto fill data tables with constant, pattern or random data
  • automatic derivatives (formula displayed)—nonlinear regression, Modeling > Nonlinear
  • automation of JMP—most of JMP can be driven by OLE automation or the JMP Scripting Language (JSL)
  • average linkage—cluster method, Multivariate Methods > Cluster
  • axial points—response surface designs or augmented, DOE, Response Surface Design
  • axis scaling—option to scale X and Y in most plots
  • axis scaling—option for central composite design, DOE, Response Surface Design

B

  • backpropogation—Modeling > Neural Net
  • bar chart—Chart option
  • Bartlett’s test for homogeneity of variance, Fit Y by X oneway
  • Bayes plot (Box-Meyer)—screen for active effects in regression model, Fit Model
  • Bayesian D-optimal design—DOE, Custom Design
  • beta fit (see fitting distributions)
  • between& within charts (see presummarize charts)
  • Bias report—Variability/Gage Chart
  • biplot (Gabriel)—3-D plot of principal components and variables, k-means clusters, Spinning Plot, Multivariate Methods > Cluster
  • binomial fitting—Distribution
  • bivariate fitting—fit mean, linear, polynomial, transformed values, spline, density ellipses, orthogonal, other (regression and curve fitting), Fit Y by X
  • Box-Behnken—(DOE), Response Surface Design
  • Box-Cox power transformation—screening designs and factor profiling, Fit Model
  • Box-Jenkins time series analysis, Modeling > Time Series
  • Box-Meyer Bayesian analysis (Bayes plot)—Fit Model
  • Box-Wilson response surface design (DOE), Response Surface Design
  • box plot—individual distribution (see quantile box plot and outlier (box & whiskers) box plot), Distribution
  • box plot option—displays sample distributions on means, Fit Y by X oneway, Control Charts
  • Brown-Forsythe test for homogeneity of variance, Fit Y by X oneway
  • Brown-Mood k-sample median test nonparametric test to compare group means, Fit Y by X oneway
  • By-group processing—process by groups, graphs and analyses appear in one window, no presorting data

C

  • calculator—(formula editor)
  • calibration—see inverse prediction and orthogonal regression
  • canonical correlation—save canonical Ys as a new data table column, Fit Model Manova
  • canonical centroid plot—shows points and multivariate means in the two dimensions that best separate the groups, Fit Model Manova
  • capability analysis—long term and short term indices, out of spec as percent and as parts per million, (PPM), Shewhart chart, histogram, quantile plot, one or more capability estimates s: long term, specified, short term grouped by fixed subgroup size, short term grouped by column, Sigma Quality (also call Process Sigma) included as a hidden column in report, Distribution
  • categorical analysis, two-way—contingency table for two categorical variables, two-way frequency table with count, total%, row%, col%, expected, deviation, and cell Chisq, Fit Y by X categorical
  • categorical model fit—nominal or ordinal response, analysis of loglikelihood Chi-square, Fit Model
  • cause-and-effect diagrams (see Diagram)
  • cell plot—displays data table cells as a matrix of rectangular colors, Cell Plot
  • censored data—right and left censoring, arbitrary censoring, survival analysis, nonlinear fitting, Survival and Reliability, Modeling > Nonlinear
  • central composite designs, DOE, Response Surface Design
  • centroid method—Multivariate Methods > Cluster
  • centroid plot—Fit Model MANOVA
  • chart—stack or overlay, bars, lines, needles; horizontal, vertical, pie chart, means with standard error bars
  • Chi-square tests—fitted distributions, Distribution
  • Chi-square tests—for general categorical response models, Wald and Likelihood ratio, Fit Model
  • Chi-square nonparametric tests—Wilcoxon, Median, Van der Waerden, Fit Model
  • Chi-square statistic—Likelihood Ratio, Pearson’s for two-way tables, Fit Y by X categorical
  • cluster analysis—hierarchical, k-means, normal mixtures clustering, geometric scale, color map, dendrogram, Self Organizing Maps (SOMS), save cluster hierarchy, biplots available for k-means cluster, Multivariate Methods > Cluster
  • Cochran-Mantel-Haenszel for testing association of X and Y variables across groups, Fit Y by X categorical
  • coefficient of variation (CV)— hidden column in Moments table and in REML and EMS results, available in data table using the Summary command, Distribution
  • collinearity—leverage plots show when model factors are linear combinations of others, Fit Model SLS
  • comparison circles—graphically shows one-way multiple comparisons, Fit Y by X Anova
  • competing risk analysis, competing causes analysis or recurrence analysis—Survival and Reliability
  • complete linkage clustering method—Multivariate Methods > Cluster
  • concatenate—append JMP data tables end to end
  • confidence curves—on scatterplot (individual and mean) for regression fits, optionally specify alpha level, Fit Y by X bivariate
  • confidence limits, individual and mean—for mean and standard deviation, save as new data table column, for inverse prediction, for nonlinear fitting
  • confounding—DOE aliasing report, Screening Design
  • confounding—shows if terms in a model are linearly related in DOE, singularity details table in Fit Model
  • contingency tables—see categorical analysis, two-way
  • contour plots—equal probability contours from 2-dimensional density estimation, Fit Y by X bivariate
  • contour plots—contours with labels, legends, color fills, predicted response within a ternary plot, response surface model effects, Contour Plot
  • contour profiler (overlayed contour plots)—Fit Model SLS, also Graph > Contour Profiler
  • contrasts—test a linear combination of parameters in a general linear model, Fit Model SLS
  • control charts—Shewhart charts (Mean, R, S, and Individual Measurement charts), UWMA and EWMA moving average charts, Cusum (Cumulative Sum) charts with V mask, charts for attribute data, p, np, c and u, Presum, Run, Levey-Jennings, Control Charts
  • Cook’s D—influence statistics, save as a new data table column, Fit Model SLS
  • coordinate exchange algorithm—create custom D-optimal designs, DOE, Custom Design
  • Correlation—bivariate scatterplot with density ellipses and report, Fit Y by X bivariate
  • correlation—many variables, pairwise report with significance probabilities, histogram of correlations (Pearson’s R, Spearman’s Rho, Kendall’s Tau, Hoeffding’s D), inverse correlation, partial correlation, scatterplot matrix with density ellipses, Multivariate Methods > Multivariate
  • correspondence analysis—graph for categorical model shows which rows and columns are similar in a two-way contingency, Fit Y by X categorical
  • Cotter designs—DOE, Screening Design
  • covariance—covariance matrix, Multivariate Methods > Multivariate
  • Cox proportional hazards model, Fit Model, Survival/Reliability > Proportional Hazard
  • Cp—selection of stepwise model (Mallow’s Cp) Fit Model Stepwise
  • Cramer-von Mises W statistic— goodness of fit statistic for one-way distribution fitting, Distribution
  • Cronbach’s alpha and standardized alpha—based on average correlation of items (item reliability analysis), Multivariate Methods > Multivariate
  • crosstabs—see categorical analysis, two-way
  • cube plot—DOE, Screening Design
  • cumulative distribution function (CDF) plot, for distribution fits, Distribution
  • cumulative logistic probability plot—logistic regression, Fit Y by X logistic
  • cumulative sum chart—Cusum control chart with V mask, Control Charts
  • curve fitting—bivariate fitting of line, polynomials, spline, and density ellipses, curves from a nonlinear fit, smooth curve fitting of histograms ° distribution fitting of histograms, Fit Y by X bivariate
  • Custom Design—create custom designs for both standard and nonstandard design situations, DOE, Custom Design
  • custom loss function—maximum likelihood estimation in nonlinear regression, Modeling > Nonlinear
  • custom tests—construct specialized tests for general linear model hypotheses, Fit Model SLS

D

  • data entry—key in data, paste from clipboard, import data, access other databases
  • D-efficiency, D-optimal designs—DOE, Custom Design
  • decision tree—see Partition
  • DPU—defect per unit analyses calculate and compare defect rates across and within groups, Graph > pareto plot
  • Deming regression—see orthogonal regression
  • dendrograms—cluster diagram, Multivariate Methods > Cluster
  • density ellipse with two variables—visualization of correlation, Fit Y by X bivariate
  • density ellipses, scatterplot matrix for many variables— visualization of correlation, Multivariate Methods > Multivariate
  • density estimation—distribution fit on histogram, equal probability contours on bivariate scatterplot, Distribution and Fit Y by X bivariate
  • derivatives—nonlinear regression, Modeling > Nonlinear
  • DOE (Design of Experiments)—commands build experimental designs for almost every situation
  • desirability profiling—prediction profile, helps visualize and optimize the response at different factor settings, optimize screening, response surface, and mixture designs, DOE, Custom Design and Fit Model SLS
  • Diagram—produces ishikawa charts, fishbone charts, cause-and effect diagram, Diagram
  • discriminant analysis—compute discriminant scores, classify points, save discriminant scores, optional stepwise selection, canonical plots, Multivariate Methods > Discriminant
  • distribution fitting—fitting, graphing, capability analysis, quantile plots for distributions: Beta, Normal, Lognormal, 2 & 3 parameter Weibull, Extreme Value, Gamma and Exponential, Binomial, Poisson, p value and power animations, tolerance Intervals computed, Distribution
  • Duncan’s multiple comparison test—not available, see Tukey-Cramer
  • Dunnett’s test—tests multiple comparison to a control group, Fit Y by X one-way
  • Durbin Watson test—test that residuals are autocorrelated, Fit Model SLS

E

  • E matrix—multivariate models Fit Model Manova
  • ED50 & LD50—nth percentile with confidence limit using logistic regression and inverse prediction, Fit Model SLS and Fit Y by X bivariate
  • editing table—standard Edit Menu commands
  • effect screening—scaled estimates, normal plot, Bayes plot, Pareto plot, Fit Model SLS
  • eigenvalues, eigenvectors—Fit Model SLS, response surface analysis
  • ellipses—bivariate density, Fit Y by X and Multivariate Methods > Multivariate
  • errors in measurement (see orthogonal regression)
  • EWMA control chart—guards against small shifts in sample means, quality control, Control Chart
  • Expected Mean Squares (EMS)—Fit Model SLS
  • experimental design—see DOE
  • exponential exploratory plot—Survival and Reliability
  • exponential fit — fitting distributions, Distribution
  • exponential model fitting—nonlinear regression with loss function, Modeling > Nonlinear
  • exponential smoothing time series forecasting— Modeling > Time Series
  • exponential survival curve analysis (see survival analysis)
  • export JMP tables (Linux)— Save As command for tab delimited text file, SAS transport, Open Office Spreadsheet
  • export JMP tables (Macintosh)— Save As command for tab delimited text file, SAS transport files, Excel file
  • export JMP tables (Windows)—Save As command for tab delimited text file, SAS transport, SAS datasets, JMP file, Excel, ODBC compliant package and Access
  • extreme value distribution fitting—nonlinear regression with loss function, Modeling > Nonlinear
  • extreme vertices design—DOE, range and linear constraints, general constraints with JSL, Mixture Design
 
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