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54:. Multivariate statistics concerns understanding the different aims and background of each of the different forms of multivariate analysis, and how they relate to each other. The practical application of multivariate statistics to a particular problem may involve several types of univariate and multivariate analyses in order to understand the relationships between variables and their relevance to the problem being studied.
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Multivariate analysis can be complicated by the desire to include physics-based analysis to calculate the effects of variables for a hierarchical "system-of-systems". Often, studies that wish to use multivariate analysis are stalled by the dimensionality of the problem. These concerns are often eased
114:) is based on the principles of multivariate statistics. Typically, MVA is used to address situations where multiple measurements are made on each experimental unit and the relations among these measurements and their structures are important. A modern, overlapping categorization of MVA includes:
187:
is similar to PCA but allows the user to extract a specified number of synthetic variables, fewer than the original set, leaving the remaining unexplained variation as error. The extracted variables are known as latent variables or factors; each one may be supposed to account for covariation in a
417:
MVA was formerly discussed solely in the context of statistical theories, due to the size and complexity of underlying datasets and its high computational consumption. With the dramatic growth of computational power, MVA now plays an increasingly important role in data analysis and has wide
197:
Redundancy analysis (RDA) is similar to canonical correlation analysis but allows the user to derive a specified number of synthetic variables from one set of (independent) variables that explain as much variance as possible in another (independent) set. It is a multivariate analogue of
214:(CCA) for summarising the joint variation in two sets of variables (like redundancy analysis); combination of correspondence analysis and multivariate regression analysis. The underlying model assumes chi-squared dissimilarities among records (cases).
928:; Anderson, T. W.; Arnold, S. F.; Eaton, M. L.; Giri, N. C.; Gnanadesikan, R.; Kendall, M. G.; Kshirsagar, A. M.; et al. (June 1986). "Review: Contemporary Textbooks on Multivariate Statistical Analysis: A Panoramic Appraisal and Critique".
181:(PCA) creates a new set of orthogonal variables that contain the same information as the original set. It rotates the axes of variation to give a new set of orthogonal axes, ordered so that they summarize decreasing proportions of the variation.
170:
Multivariate regression attempts to determine a formula that can describe how elements in a vector of variables respond simultaneously to changes in others. For linear relations, regression analyses here are based on forms of the
92:
usually considered to be special cases of multivariate statistics because the analysis is dealt with by considering the (univariate) conditional distribution of a single outcome variable given the other variables.
136:, highly accurate approximations of the physics-based code. Since surrogate models take the form of an equation, they can be evaluated very quickly. This becomes an enabler for large-scale MVA studies: while a
208:(CA), or reciprocal averaging, finds (like PCA) a set of synthetic variables that summarise the original set. The underlying model assumes chi-squared dissimilarities among records (cases).
292:
consists in replacing a correlation matrix by a diagram where the âremarkableâ correlations are represented by a solid line (positive correlation), or a dotted line (negative correlation).
1154:
Izenman, Alan J. (2008). Modern
Multivariate Statistical Techniques: Regression, Classification, and Manifold Learning. Springer Texts in Statistics. New York: Springer-Verlag.
930:
175:. Some suggest that multivariate regression is distinct from multivariable regression, however, that is debated and not consistently true across scientific fields.
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analysis (PRC) is a method based on RDA that allows the user to focus on treatment effects over time by correcting for changes in control treatments over time.
242:
assign objects into groups (called clusters) so that objects (cases) from the same cluster are more similar to each other than objects from different clusters.
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comprises various algorithms to determine a set of synthetic variables that best represent the pairwise distances between records. The original method is
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230:, or canonical variate analysis, attempts to establish whether a set of variables can be used to distinguish between two or more groups of cases.
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across the design space is difficult with physics-based codes, it becomes trivial when evaluating surrogate models, which often take the form of
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creates a decision tree that attempts to correctly classify members of the population based on a dichotomous dependent variable.
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finds linear relationships among two sets of variables; it is the generalised (i.e. canonical) version of bivariate correlation.
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305:. Rather than discarding the whole data point, it is common to "fill in" values for the missing components, a process called "
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236:(LDA) computes a linear predictor from two sets of normally distributed data to allow for classification of new observations.
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It is very common that in an experimentally acquired set of data the values of some components of a given data point are
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used in multivariate analyses that play a similar role to the corresponding set of distributions that are used in
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Van Den
Wollenberg, Arnold L. (1977). "Redundancy analysis an alternative for canonical correlation analysis".
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Malakooti, B. (2013). Operations and
Production Systems with Multiple Objectives. John Wiley & Sons.
630:
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There are an enormous number of software packages and other tools for multivariate analysis, including:
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to cover cases where there is more than one dependent variable to be analyzed simultaneously; see also
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involve more than one regression equation, with different dependent variables, estimated together.
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Unsophisticated analysts of bivariate
Gaussian problems may find useful a crude but accurate
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390:, educated a generation of theorists and applied statisticians; Anderson's book emphasizes
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1980:
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74:, particularly where several different quantities are of interest to the same analysis.
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849:
Canoco reference manual and user's guide: software for ordination (version 5.0)
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254:
extend regression and clustering methods to non-linear multivariate models.
152:
Many different models are used in MVA, each with its own type of analysis:
30:"Multivariate analysis" redirects here. For the usage in mathematics, see
1958:
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549:
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encompassing the simultaneous observation and analysis of more than one
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27:
Simultaneous observation and analysis of more than one outcome variable
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67:
how these can be used to represent the distributions of observed data;
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2340:
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1571:
1362:
1168:
Handbook of
Applied Multivariate Statistics and Mathematical Modeling
559:
554:
1025:
has details on the packages available for multivariate data analysis
943:
57:
In addition, multivariate statistics is concerned with multivariate
1087:
788:
329:
is appropriate to a dataset. These multivariate distributions are:
80:
Certain types of problems involving multivariate data, for example
711:
International
Encyclopedia of the Social & Behavioral Sciences
529:
515:
419:
1204:
1305:
1210:
InsightsNow: Makers of
ReportsNow, ProfilesNow, and KnowledgeNow
524:
500:
264:, scatterplot matrices can be used to explore multivariate data.
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2588:
1887:
1657:
1274:
1218:
1200:
Statnotes: Topics in
Multivariate Analysis, by G. David Garson
118:
Normal and general multivariate models and distribution theory
1214:
1209:
1080:
Regression
Analysis — Theory, Methods, and Applications
791:
of accurately gauging probability by simply taking the sum
811:- 2) and taking the inverse anti-ln of half that product.
1166:
Tinsley, Howard E. A.; Brown, Steven D., eds. (2000).
582:
280:
variables on their own and each other's lagged values.
3540:
3127:
Autoregressive conditional heteroskedasticity (ARCH)
1101:
388:
An Introduction to Multivariate Statistical Analysis
212:
Canonical (or "constrained") correspondence analysis
124:
Probability computations of multidimensional regions
3434:
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3224:
3191:
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1468:
1424:
1376:
1296:
1287:
847:ter Braak, Cajo J.F. & Ć milauer, Petr (2012).
2675:Multivariate adaptive regression splines (MARS)
1082:, Springer-Verlag, Berlin, 2011 (4th printing).
931:Journal of the American Statistical Association
709:, in Smelser, Neil J.; Baltes, Paul B. (eds.),
601:Important publications in multivariate analysis
127:The exploration of data structures and patterns
1038:Johnson, Richard A.; Wichern, Dean W. (2007).
1230:
673:Soft independent modelling of class analogies
370:is a multivariate distribution, generalising
276:involves simultaneous regressions of various
8:
741:"Multivariate or multivariable regression?"
3284:
3271:
3188:
2994:
2863:
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2585:
2313:
2096:
1897:
1884:
1667:
1654:
1293:
1284:
1271:
1237:
1223:
1215:
1107:KV Mardia; JT Kent & JM Bibby (1979).
451:Classification and discrimination analysis
121:The study and measurement of relationships
1040:Applied Multivariate Statistical Analysis
991:
764:
1142:Analysis of Incomplete Multivariate Data
1135:Multivariate Data Analysis with Readings
890:An Introduction to Multivariate Analysis
863:Analysis of Incomplete Multivariate Data
851:, p292. Microcomputer Power, Ithaca, NY.
803:at minimum, dividing this difference by
799:residuals' squares, subtracting the sum
705:Olkin, I.; Sampson, A. R. (2001-01-01),
3547:
1130:. New Haven, CT: Yale University Press.
694:
364:Bayesian multivariate linear regression
3201:KaplanâMeier estimator (product limit)
1089:Interactive Graphics for Data Analysis
581:DataPandit (Free SaaS applications by
1109:Multivariate Analysis. Academic Press
611:Structured data analysis (statistics)
7:
3511:
3211:Accelerated failure time (AFT) model
1205:Mike Palmer: The Ordination Web Page
974:Schervish, Mark J. (November 1987).
700:
698:
3523:
2806:Analysis of variance (ANOVA, anova)
976:"A Review of Multivariate Analysis"
346:Multivariate Student-t distribution
313:Important probability distributions
165:Multivariate analysis of covariance
2901:CochranâMantelâHaenszel statistics
1527:Pearson product-moment correlation
1176:10.1016/B978-0-12-691360-6.X5000-9
1123:(M.A. level "likelihood" approach)
713:, Pergamon, pp. 10240â10247,
368:Hotelling's T-squared distribution
25:
1042:(Sixth ed.). Prentice Hall.
707:"Multivariate Analysis: Overview"
606:Multivariate testing in marketing
596:Estimation of covariance matrices
157:Multivariate analysis of variance
3550:
3522:
3510:
3498:
3485:
3484:
652:Partial least squares regression
573:is a multivariate analysis tool.
447:Multivariate regression analysis
336:Multivariate normal distribution
70:how they can be used as part of
3160:Least-squares spectral analysis
1149:Applied Multivariate Techniques
739:Hidalgo, B; Goodman, M (2013).
583:Let's Excel Analytics Solutions
567:includes multivariate analysis.
431:Multivariate hypothesis testing
374:, that is used in multivariate
2141:Mean-unbiased minimum-variance
222:principal coordinates analysis
192:Canonical correlation analysis
1:
3454:Geographic information system
2670:Simultaneous equations models
807:, multiplying the result by (
268:Simultaneous equations models
179:Principal components analysis
51:multivariate random variables
2637:Coefficient of determination
2248:Uniformly most powerful test
1151:. Wiley. (Informal, applied)
1060:; JT Kent; JM Bibby (1979).
662:Principal component analysis
616:Structural equation modeling
356:Inverse-Wishart distribution
297:Dealing with incomplete data
234:Linear discriminant analysis
188:group of observed variables.
3206:Proportional hazards models
3150:Spectral density estimation
3132:Vector autoregression (VAR)
2566:Maximum posterior estimator
1798:Randomized controlled trial
565:NCSS (statistical software)
290:Iconography of correlations
3589:
2966:Multivariate distributions
1386:Average absolute deviation
865:. Chapman & Hall/CRC.
486:JMP (statistical software)
439:Latent structure discovery
252:Artificial neural networks
100:
29:
3480:
3283:
3270:
2954:Structural equation model
2862:
2837:
2608:
2584:
2316:
2290:Score/Lagrange multiplier
1896:
1883:
1705:Sample size determination
1666:
1653:
1283:
1270:
1252:
642:Exploratory data analysis
461:Multidimensional analysis
386:Anderson's 1958 textbook,
319:probability distributions
284:Principal response curves
262:parallel coordinate plots
59:probability distributions
3449:Environmental statistics
2971:Elliptical distributions
2764:Generalized linear model
2693:Simple linear regression
2463:HodgesâLehmann estimator
1920:Probability distribution
1829:Stochastic approximation
1391:Coefficient of variation
1137:, 4th ed. Prentice-Hall.
1126:Feinstein, A. R. (1996)
1103:, Wiley, New York, 1958.
757:10.2105/AJPH.2012.300897
679:Statistical interference
466:Multidimensional scaling
435:Dimensionality reduction
372:Student's t-distribution
218:Multidimensional scaling
82:simple linear regression
3573:Multivariate statistics
3109:Cross-correlation (XCF)
2717:Non-standard predictors
2151:LehmannâScheffĂ© theorem
1824:Adaptive clinical trial
1144:. CRC Press. (Advanced)
1133:Hair, J. F. Jr. (1995)
1078:A. Sen, M. Srivastava,
206:Correspondence analysis
38:Multivariate statistics
3505:Mathematics portal
3326:Engineering statistics
3234:NelsonâAalen estimator
2811:Analysis of covariance
2698:Ordinary least squares
2622:Pearson product-moment
2026:Statistical functional
1937:Empirical distribution
1770:Controlled experiments
1499:Frequency distribution
1277:Descriptive statistics
1140:Schafer, J. L. (1997)
1128:Multivariable Analysis
398:and the properties of
396:likelihood ratio tests
246:Recursive partitioning
138:Monte Carlo simulation
32:Multivariable calculus
3421:Population statistics
3363:System identification
3097:Autocorrelation (ACF)
3025:Exponential smoothing
2939:Discriminant analysis
2934:Canonical correlation
2798:Partition of variance
2660:Regression validation
2504:(JonckheereâTerpstra)
2403:Likelihood-ratio test
2092:Frequentist inference
2004:Locationâscale family
1925:Sampling distribution
1890:Statistical inference
1857:Cross-sectional study
1844:Observational studies
1803:Randomized experiment
1632:Stem-and-leaf display
1434:Central limit theorem
1086:Cook, Swayne (2007).
1062:Multivariate Analysis
993:10.1214/ss/1177013111
861:J.L. Schafer (1997).
631:Design of experiments
274:Vector autoregression
228:Discriminant analysis
224:(PCoA; based on PCA).
159:(MANOVA) extends the
108:Multivariate analysis
97:Multivariate analysis
72:statistical inference
18:Multivariate Analysis
3344:Probabilistic design
2929:Principal components
2772:Exponential families
2724:Nonlinear regression
2703:General linear model
2665:Mixed effects models
2655:Errors and residuals
2632:Confounding variable
2534:Bayesian probability
2512:Van der Waerden test
2502:Ordered alternative
2267:Multiple comparisons
2146:RaoâBlackwellization
2109:Estimating equations
2065:Statistical distance
1783:Factorial experiment
1316:Arithmetic-Geometric
637:Dimensional analysis
341:Wishart distribution
258:Statistical graphics
173:general linear model
161:analysis of variance
40:is a subdivision of
3416:Official statistics
3339:Methods engineering
3020:Seasonal adjustment
2788:Poisson regressions
2708:Bayesian regression
2647:Regression analysis
2627:Partial correlation
2599:Regression analysis
2198:Prediction interval
2193:Likelihood interval
2183:Confidence interval
2175:Interval estimation
2136:Unbiased estimators
1954:Model specification
1834:Up-and-down designs
1522:Partial correlation
1478:Index of dispersion
1396:Interquartile range
980:Statistical Science
684:Univariate analysis
668:Regression analysis
657:Pattern recognition
327:normal distribution
323:univariate analysis
132:through the use of
103:Univariate analysis
86:multiple regression
61:, in terms of both
3436:Spatial statistics
3316:Medical statistics
3216:First hitting time
3170:Whittle likelihood
2821:Degrees of freedom
2816:Multivariate ANOVA
2749:Heteroscedasticity
2561:Bayesian estimator
2526:Bayesian inference
2375:KolmogorovâSmirnov
2260:Randomization test
2230:Testing hypotheses
2203:Tolerance interval
2114:Maximum likelihood
2009:Exponential family
1942:Density estimation
1902:Statistical theory
1862:Natural experiment
1808:Scientific control
1725:Survey methodology
1411:Standard deviation
1170:. Academic Press.
1147:Sharma, S. (1996)
1064:. Academic Press.
892:, New York: Wiley
835:10.1007/BF02294050
745:Am J Public Health
626:Bivariate analysis
571:The UnscramblerÂź X
477:Software and tools
456:Variable selection
392:hypothesis testing
376:hypothesis testing
360:Bayesian inference
317:There is a set of
240:Clustering systems
3538:
3537:
3476:
3475:
3472:
3471:
3411:National accounts
3381:Actuarial science
3373:Social statistics
3266:
3265:
3262:
3261:
3258:
3257:
3193:Survival function
3178:
3177:
3040:Granger causality
2881:Contingency table
2856:Survival analysis
2833:
2832:
2829:
2828:
2685:Linear regression
2580:
2579:
2576:
2575:
2551:Credible interval
2520:
2519:
2303:
2302:
2119:Method of moments
1988:Parametric family
1949:Statistical model
1879:
1878:
1875:
1874:
1793:Random assignment
1715:Statistical power
1649:
1648:
1645:
1644:
1494:Contingency table
1464:
1463:
1331:Generalized/power
1185:978-0-12-691360-6
1049:978-0-13-187715-3
926:Sen, Pranab Kumar
872:978-1-4398-2186-2
362:, for example in
148:Types of analysis
16:(Redirected from
3580:
3555:
3554:
3546:
3526:
3525:
3514:
3513:
3503:
3502:
3488:
3487:
3391:Crime statistics
3285:
3272:
3189:
3155:Fourier analysis
3142:Frequency domain
3122:
3069:
3035:Structural break
2995:
2944:Cluster analysis
2891:Log-linear model
2864:
2839:
2780:
2754:Homoscedasticity
2610:
2586:
2505:
2497:
2489:
2488:(KruskalâWallis)
2473:
2458:
2413:Cross validation
2398:
2380:AndersonâDarling
2327:
2314:
2285:Likelihood-ratio
2277:Parametric tests
2255:Permutation test
2238:1- & 2-tails
2129:Minimum distance
2101:Point estimation
2097:
2048:Optimal decision
1999:
1898:
1885:
1867:Quasi-experiment
1817:Adaptive designs
1668:
1655:
1532:Rank correlation
1294:
1285:
1272:
1239:
1232:
1225:
1216:
1189:
1122:
1099:T. W. Anderson,
1093:
1075:
1053:
1026:
1020:
1014:
1013:
995:
971:
965:
963:
938:(394): 560â564.
922:
916:
883:
877:
876:
858:
852:
845:
839:
838:
818:
812:
785:
779:
778:
768:
736:
730:
729:
728:
727:
702:
366:. Additionally,
358:is important in
142:response-surface
134:surrogate models
46:outcome variable
21:
3588:
3587:
3583:
3582:
3581:
3579:
3578:
3577:
3563:
3562:
3561:
3549:
3541:
3539:
3534:
3497:
3468:
3430:
3367:
3353:quality control
3320:
3302:Clinical trials
3279:
3254:
3238:
3226:Hazard function
3220:
3174:
3136:
3120:
3083:
3079:BreuschâGodfrey
3067:
3044:
2984:
2959:Factor analysis
2905:
2886:Graphical model
2858:
2825:
2792:
2778:
2758:
2712:
2679:
2641:
2604:
2603:
2572:
2516:
2503:
2495:
2487:
2471:
2456:
2435:Rank statistics
2429:
2408:Model selection
2396:
2354:Goodness of fit
2348:
2325:
2299:
2271:
2224:
2169:
2158:Median unbiased
2086:
1997:
1930:Order statistic
1892:
1871:
1838:
1812:
1764:
1719:
1662:
1660:Data collection
1641:
1553:
1508:
1482:
1460:
1420:
1372:
1289:Continuous data
1279:
1266:
1248:
1243:
1196:
1186:
1165:
1119:
1106:
1085:
1072:
1056:
1050:
1037:
1034:
1032:Further reading
1029:
1021:
1017:
973:
972:
968:
964:(Pages 560â561)
944:10.2307/2289251
924:
923:
919:
884:
880:
873:
860:
859:
855:
846:
842:
820:
819:
815:
786:
782:
738:
737:
733:
725:
723:
721:
704:
703:
696:
692:
592:
540:The Unscrambler
479:
428:
418:application in
400:power functions
384:
315:
299:
260:such as tours,
185:Factor analysis
150:
105:
99:
35:
28:
23:
22:
15:
12:
11:
5:
3586:
3584:
3576:
3575:
3565:
3564:
3560:
3559:
3536:
3535:
3533:
3532:
3520:
3508:
3494:
3481:
3478:
3477:
3474:
3473:
3470:
3469:
3467:
3466:
3461:
3456:
3451:
3446:
3440:
3438:
3432:
3431:
3429:
3428:
3423:
3418:
3413:
3408:
3403:
3398:
3393:
3388:
3383:
3377:
3375:
3369:
3368:
3366:
3365:
3360:
3355:
3346:
3341:
3336:
3330:
3328:
3322:
3321:
3319:
3318:
3313:
3308:
3299:
3297:Bioinformatics
3293:
3291:
3281:
3280:
3275:
3268:
3267:
3264:
3263:
3260:
3259:
3256:
3255:
3253:
3252:
3246:
3244:
3240:
3239:
3237:
3236:
3230:
3228:
3222:
3221:
3219:
3218:
3213:
3208:
3203:
3197:
3195:
3186:
3180:
3179:
3176:
3175:
3173:
3172:
3167:
3162:
3157:
3152:
3146:
3144:
3138:
3137:
3135:
3134:
3129:
3124:
3116:
3111:
3106:
3105:
3104:
3102:partial (PACF)
3093:
3091:
3085:
3084:
3082:
3081:
3076:
3071:
3063:
3058:
3052:
3050:
3049:Specific tests
3046:
3045:
3043:
3042:
3037:
3032:
3027:
3022:
3017:
3012:
3007:
3001:
2999:
2992:
2986:
2985:
2983:
2982:
2981:
2980:
2979:
2978:
2963:
2962:
2961:
2951:
2949:Classification
2946:
2941:
2936:
2931:
2926:
2921:
2915:
2913:
2907:
2906:
2904:
2903:
2898:
2896:McNemar's test
2893:
2888:
2883:
2878:
2872:
2870:
2860:
2859:
2842:
2835:
2834:
2831:
2830:
2827:
2826:
2824:
2823:
2818:
2813:
2808:
2802:
2800:
2794:
2793:
2791:
2790:
2774:
2768:
2766:
2760:
2759:
2757:
2756:
2751:
2746:
2741:
2736:
2734:Semiparametric
2731:
2726:
2720:
2718:
2714:
2713:
2711:
2710:
2705:
2700:
2695:
2689:
2687:
2681:
2680:
2678:
2677:
2672:
2667:
2662:
2657:
2651:
2649:
2643:
2642:
2640:
2639:
2634:
2629:
2624:
2618:
2616:
2606:
2605:
2602:
2601:
2596:
2590:
2589:
2582:
2581:
2578:
2577:
2574:
2573:
2571:
2570:
2569:
2568:
2558:
2553:
2548:
2547:
2546:
2541:
2530:
2528:
2522:
2521:
2518:
2517:
2515:
2514:
2509:
2508:
2507:
2499:
2491:
2475:
2472:(MannâWhitney)
2467:
2466:
2465:
2452:
2451:
2450:
2439:
2437:
2431:
2430:
2428:
2427:
2426:
2425:
2420:
2415:
2405:
2400:
2397:(ShapiroâWilk)
2392:
2387:
2382:
2377:
2372:
2364:
2358:
2356:
2350:
2349:
2347:
2346:
2338:
2329:
2317:
2311:
2309:Specific tests
2305:
2304:
2301:
2300:
2298:
2297:
2292:
2287:
2281:
2279:
2273:
2272:
2270:
2269:
2264:
2263:
2262:
2252:
2251:
2250:
2240:
2234:
2232:
2226:
2225:
2223:
2222:
2221:
2220:
2215:
2205:
2200:
2195:
2190:
2185:
2179:
2177:
2171:
2170:
2168:
2167:
2162:
2161:
2160:
2155:
2154:
2153:
2148:
2133:
2132:
2131:
2126:
2121:
2116:
2105:
2103:
2094:
2088:
2087:
2085:
2084:
2079:
2074:
2073:
2072:
2062:
2057:
2056:
2055:
2045:
2044:
2043:
2038:
2033:
2023:
2018:
2013:
2012:
2011:
2006:
2001:
1985:
1984:
1983:
1978:
1973:
1963:
1962:
1961:
1956:
1946:
1945:
1944:
1934:
1933:
1932:
1922:
1917:
1912:
1906:
1904:
1894:
1893:
1888:
1881:
1880:
1877:
1876:
1873:
1872:
1870:
1869:
1864:
1859:
1854:
1848:
1846:
1840:
1839:
1837:
1836:
1831:
1826:
1820:
1818:
1814:
1813:
1811:
1810:
1805:
1800:
1795:
1790:
1785:
1780:
1774:
1772:
1766:
1765:
1763:
1762:
1760:Standard error
1757:
1752:
1747:
1746:
1745:
1740:
1729:
1727:
1721:
1720:
1718:
1717:
1712:
1707:
1702:
1697:
1692:
1690:Optimal design
1687:
1682:
1676:
1674:
1664:
1663:
1658:
1651:
1650:
1647:
1646:
1643:
1642:
1640:
1639:
1634:
1629:
1624:
1619:
1614:
1609:
1604:
1599:
1594:
1589:
1584:
1579:
1574:
1569:
1563:
1561:
1555:
1554:
1552:
1551:
1546:
1545:
1544:
1539:
1529:
1524:
1518:
1516:
1510:
1509:
1507:
1506:
1501:
1496:
1490:
1488:
1487:Summary tables
1484:
1483:
1481:
1480:
1474:
1472:
1466:
1465:
1462:
1461:
1459:
1458:
1457:
1456:
1451:
1446:
1436:
1430:
1428:
1422:
1421:
1419:
1418:
1413:
1408:
1403:
1398:
1393:
1388:
1382:
1380:
1374:
1373:
1371:
1370:
1365:
1360:
1359:
1358:
1353:
1348:
1343:
1338:
1333:
1328:
1323:
1321:Contraharmonic
1318:
1313:
1302:
1300:
1291:
1281:
1280:
1275:
1268:
1267:
1265:
1264:
1259:
1253:
1250:
1249:
1244:
1242:
1241:
1234:
1227:
1219:
1213:
1212:
1207:
1202:
1195:
1194:External links
1192:
1191:
1190:
1184:
1163:
1152:
1145:
1138:
1131:
1124:
1118:978-0124712522
1117:
1104:
1097:
1094:
1083:
1076:
1070:
1054:
1048:
1033:
1030:
1028:
1027:
1015:
986:(4): 396â413.
966:
917:
878:
871:
853:
840:
829:(2): 207â219.
813:
780:
731:
719:
693:
691:
688:
687:
686:
681:
676:
670:
665:
659:
654:
649:
644:
639:
634:
628:
623:
621:RV coefficient
618:
613:
608:
603:
598:
591:
588:
587:
586:
579:
574:
568:
562:
557:
552:
547:
542:
537:
532:
527:
522:
513:
511:SAS (software)
508:
503:
498:
493:
488:
478:
475:
474:
473:
468:
463:
458:
453:
448:
445:
440:
437:
432:
427:
424:
383:
380:
352:
351:
350:
349:
343:
338:
314:
311:
298:
295:
294:
293:
287:
281:
271:
265:
255:
249:
243:
237:
231:
225:
215:
209:
203:
195:
189:
182:
176:
168:
149:
146:
129:
128:
125:
122:
119:
98:
95:
78:
77:
76:
75:
68:
26:
24:
14:
13:
10:
9:
6:
4:
3:
2:
3585:
3574:
3571:
3570:
3568:
3558:
3553:
3548:
3544:
3531:
3530:
3521:
3519:
3518:
3509:
3507:
3506:
3501:
3495:
3493:
3492:
3483:
3482:
3479:
3465:
3462:
3460:
3459:Geostatistics
3457:
3455:
3452:
3450:
3447:
3445:
3442:
3441:
3439:
3437:
3433:
3427:
3426:Psychometrics
3424:
3422:
3419:
3417:
3414:
3412:
3409:
3407:
3404:
3402:
3399:
3397:
3394:
3392:
3389:
3387:
3384:
3382:
3379:
3378:
3376:
3374:
3370:
3364:
3361:
3359:
3356:
3354:
3350:
3347:
3345:
3342:
3340:
3337:
3335:
3332:
3331:
3329:
3327:
3323:
3317:
3314:
3312:
3309:
3307:
3303:
3300:
3298:
3295:
3294:
3292:
3290:
3289:Biostatistics
3286:
3282:
3278:
3273:
3269:
3251:
3250:Log-rank test
3248:
3247:
3245:
3241:
3235:
3232:
3231:
3229:
3227:
3223:
3217:
3214:
3212:
3209:
3207:
3204:
3202:
3199:
3198:
3196:
3194:
3190:
3187:
3185:
3181:
3171:
3168:
3166:
3163:
3161:
3158:
3156:
3153:
3151:
3148:
3147:
3145:
3143:
3139:
3133:
3130:
3128:
3125:
3123:
3121:(BoxâJenkins)
3117:
3115:
3112:
3110:
3107:
3103:
3100:
3099:
3098:
3095:
3094:
3092:
3090:
3086:
3080:
3077:
3075:
3074:DurbinâWatson
3072:
3070:
3064:
3062:
3059:
3057:
3056:DickeyâFuller
3054:
3053:
3051:
3047:
3041:
3038:
3036:
3033:
3031:
3030:Cointegration
3028:
3026:
3023:
3021:
3018:
3016:
3013:
3011:
3008:
3006:
3005:Decomposition
3003:
3002:
3000:
2996:
2993:
2991:
2987:
2977:
2974:
2973:
2972:
2969:
2968:
2967:
2964:
2960:
2957:
2956:
2955:
2952:
2950:
2947:
2945:
2942:
2940:
2937:
2935:
2932:
2930:
2927:
2925:
2922:
2920:
2917:
2916:
2914:
2912:
2908:
2902:
2899:
2897:
2894:
2892:
2889:
2887:
2884:
2882:
2879:
2877:
2876:Cohen's kappa
2874:
2873:
2871:
2869:
2865:
2861:
2857:
2853:
2849:
2845:
2840:
2836:
2822:
2819:
2817:
2814:
2812:
2809:
2807:
2804:
2803:
2801:
2799:
2795:
2789:
2785:
2781:
2775:
2773:
2770:
2769:
2767:
2765:
2761:
2755:
2752:
2750:
2747:
2745:
2742:
2740:
2737:
2735:
2732:
2730:
2729:Nonparametric
2727:
2725:
2722:
2721:
2719:
2715:
2709:
2706:
2704:
2701:
2699:
2696:
2694:
2691:
2690:
2688:
2686:
2682:
2676:
2673:
2671:
2668:
2666:
2663:
2661:
2658:
2656:
2653:
2652:
2650:
2648:
2644:
2638:
2635:
2633:
2630:
2628:
2625:
2623:
2620:
2619:
2617:
2615:
2611:
2607:
2600:
2597:
2595:
2592:
2591:
2587:
2583:
2567:
2564:
2563:
2562:
2559:
2557:
2554:
2552:
2549:
2545:
2542:
2540:
2537:
2536:
2535:
2532:
2531:
2529:
2527:
2523:
2513:
2510:
2506:
2500:
2498:
2492:
2490:
2484:
2483:
2482:
2479:
2478:Nonparametric
2476:
2474:
2468:
2464:
2461:
2460:
2459:
2453:
2449:
2448:Sample median
2446:
2445:
2444:
2441:
2440:
2438:
2436:
2432:
2424:
2421:
2419:
2416:
2414:
2411:
2410:
2409:
2406:
2404:
2401:
2399:
2393:
2391:
2388:
2386:
2383:
2381:
2378:
2376:
2373:
2371:
2369:
2365:
2363:
2360:
2359:
2357:
2355:
2351:
2345:
2343:
2339:
2337:
2335:
2330:
2328:
2323:
2319:
2318:
2315:
2312:
2310:
2306:
2296:
2293:
2291:
2288:
2286:
2283:
2282:
2280:
2278:
2274:
2268:
2265:
2261:
2258:
2257:
2256:
2253:
2249:
2246:
2245:
2244:
2241:
2239:
2236:
2235:
2233:
2231:
2227:
2219:
2216:
2214:
2211:
2210:
2209:
2206:
2204:
2201:
2199:
2196:
2194:
2191:
2189:
2186:
2184:
2181:
2180:
2178:
2176:
2172:
2166:
2163:
2159:
2156:
2152:
2149:
2147:
2144:
2143:
2142:
2139:
2138:
2137:
2134:
2130:
2127:
2125:
2122:
2120:
2117:
2115:
2112:
2111:
2110:
2107:
2106:
2104:
2102:
2098:
2095:
2093:
2089:
2083:
2080:
2078:
2075:
2071:
2068:
2067:
2066:
2063:
2061:
2058:
2054:
2053:loss function
2051:
2050:
2049:
2046:
2042:
2039:
2037:
2034:
2032:
2029:
2028:
2027:
2024:
2022:
2019:
2017:
2014:
2010:
2007:
2005:
2002:
2000:
1994:
1991:
1990:
1989:
1986:
1982:
1979:
1977:
1974:
1972:
1969:
1968:
1967:
1964:
1960:
1957:
1955:
1952:
1951:
1950:
1947:
1943:
1940:
1939:
1938:
1935:
1931:
1928:
1927:
1926:
1923:
1921:
1918:
1916:
1913:
1911:
1908:
1907:
1905:
1903:
1899:
1895:
1891:
1886:
1882:
1868:
1865:
1863:
1860:
1858:
1855:
1853:
1850:
1849:
1847:
1845:
1841:
1835:
1832:
1830:
1827:
1825:
1822:
1821:
1819:
1815:
1809:
1806:
1804:
1801:
1799:
1796:
1794:
1791:
1789:
1786:
1784:
1781:
1779:
1776:
1775:
1773:
1771:
1767:
1761:
1758:
1756:
1755:Questionnaire
1753:
1751:
1748:
1744:
1741:
1739:
1736:
1735:
1734:
1731:
1730:
1728:
1726:
1722:
1716:
1713:
1711:
1708:
1706:
1703:
1701:
1698:
1696:
1693:
1691:
1688:
1686:
1683:
1681:
1678:
1677:
1675:
1673:
1669:
1665:
1661:
1656:
1652:
1638:
1635:
1633:
1630:
1628:
1625:
1623:
1620:
1618:
1615:
1613:
1610:
1608:
1605:
1603:
1600:
1598:
1595:
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1582:Control chart
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886:T.W. Anderson
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823:Psychometrika
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3527:
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3496:
3489:
3401:Econometrics
3351: /
3334:Chemometrics
3311:Epidemiology
3304: /
3277:Applications
3119:ARIMA model
3066:Q-statistic
3015:Stationarity
2911:Multivariate
2910:
2854: /
2850: /
2848:Multivariate
2847:
2846: /
2786: /
2782: /
2556:Bayes factor
2455:Signed rank
2367:
2341:
2333:
2321:
2016:Completeness
1852:Cohort study
1750:Opinion poll
1685:Missing data
1672:Study design
1627:Scatter plot
1549:Scatter plot
1542:Spearman's Ï
1504:Grouped data
1167:
1148:
1141:
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1127:
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1100:
1088:
1079:
1061:
1039:
1018:
983:
979:
969:
935:
929:
920:
908:; 3e (2003)
900:; 2e (1984)
889:
881:
862:
856:
848:
843:
826:
822:
816:
808:
804:
800:
796:
792:
783:
751:(1): 39â40.
748:
744:
734:
724:, retrieved
710:
480:
426:Applications
416:
412:monotonicity
408:unbiasedness
387:
385:
353:
316:
300:
151:
130:
111:
107:
106:
89:
79:
56:
49:
37:
36:
3557:Mathematics
3529:WikiProject
3444:Cartography
3406:Jurimetrics
3358:Reliability
3089:Time domain
3068:(LjungâBox)
2990:Time-series
2868:Categorical
2852:Time-series
2844:Categorical
2779:(Bernoulli)
2614:Correlation
2594:Correlation
2390:JarqueâBera
2362:Chi-squared
2124:M-estimator
2077:Asymptotics
2021:Sufficiency
1788:Interaction
1700:Replication
1680:Effect size
1637:Violin plot
1617:Radar chart
1597:Forest plot
1587:Correlogram
1537:Kendall's Ï
471:Data mining
278:time series
144:equations.
3396:Demography
3114:ARMA model
2919:Regression
2496:(Friedman)
2457:(Wilcoxon)
2395:Normality
2385:Lilliefors
2332:Student's
2208:Resampling
2082:Robustness
2070:divergence
2060:Efficiency
1998:(monotone)
1993:Likelihood
1910:Population
1743:Stratified
1695:Population
1514:Dependence
1470:Count data
1401:Percentile
1378:Dispersion
1311:Arithmetic
1246:Statistics
914:0471360910
906:0471889873
898:0471026409
726:2019-09-02
690:References
535:STATISTICA
443:Clustering
307:imputation
200:regression
167:(MANCOVA).
101:See also:
42:statistics
2777:Logistic
2544:posterior
2470:Rank sum
2218:Jackknife
2213:Bootstrap
2031:Bootstrap
1966:Parameter
1915:Statistic
1710:Statistic
1622:Run chart
1607:Pie chart
1602:Histogram
1592:Fan chart
1567:Bar chart
1449:L-moments
1336:Geometric
1058:KV Mardia
1002:0883-4237
952:0162-1459
325:when the
3567:Category
3491:Category
3184:Survival
3061:Johansen
2784:Binomial
2739:Isotonic
2326:(normal)
1971:location
1778:Blocking
1733:Sampling
1612:QâQ plot
1577:Box plot
1559:Graphics
1454:Skewness
1444:Kurtosis
1416:Variance
1346:Heronian
1341:Harmonic
775:23153131
590:See also
550:SmartPLS
422:fields.
48:, i.e.,
3517:Commons
3464:Kriging
3349:Process
3306:studies
3165:Wavelet
2998:General
2165:Plug-in
1959:L space
1738:Cluster
1439:Moments
1257:Outline
1010:2245530
960:2289251
888:(1958)
795:of the
766:3518362
675:(SIMCA)
545:WarpPLS
491:MiniTab
382:History
303:missing
3543:Portal
3386:Census
2976:Normal
2924:Manova
2744:Robust
2494:2-way
2486:1-way
2324:-test
1995:
1572:Biplot
1363:Median
1356:Lehmer
1298:Center
1182:
1158:
1115:
1068:
1046:
1008:
1000:
958:
950:
912:
904:
896:
869:
789:method
773:
763:
717:
560:Eviews
555:MATLAB
520:Python
88:, are
3010:Trend
2539:prior
2481:anova
2370:-test
2344:-test
2336:-test
2243:Power
2188:Pivot
1981:shape
1976:scale
1426:Shape
1406:Range
1351:Heinz
1326:Cubic
1262:Index
1006:JSTOR
956:JSTOR
664:(PCA)
633:(DoE)
577:SIMCA
530:Stata
516:SciPy
420:Omics
3243:Test
2443:Sign
2295:Wald
1368:Mode
1306:Mean
1180:ISBN
1156:ISBN
1113:ISBN
1066:ISBN
1044:ISBN
1023:CRAN
998:ISSN
948:ISSN
910:ISBN
902:ISBN
894:ISBN
867:ISBN
771:PMID
715:ISBN
525:SPSS
518:for
501:PSPP
496:Calc
410:and
394:via
354:The
84:and
2423:BIC
2418:AIC
1172:doi
988:doi
940:doi
831:doi
761:PMC
753:doi
749:103
647:OLS
309:".
112:MVA
90:not
3569::
1178:.
1111:.
1004:.
996:.
982:.
978:.
954:.
946:.
936:81
934:.
827:42
825:.
805:Sm
801:Sm
769:.
759:.
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743:.
697:^
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406:,
402::
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1174::
1162:.
1121:.
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1052:.
1012:.
990::
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875:.
837:.
833::
809:N
797:N
793:S
777:.
755::
585:)
506:R
348:.
202:.
110:(
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20:)
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