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VOStat Statistical Analysis for the Virtual Observatory Start using VOStat right now

VOStat: FAQ

Plotting:

• 1-, 2- and 3-dimensional plots.
• Interactive 3-dimensional graphics.
• Various summary plots, like histograms, boxplots and dotcharts.
• Circular plots for directional data.
• Variogram for spatial data.

Summarization:

• Computation of simple statistics, like mean, variance etc.
• Summary statistics for directional data.

Fitting distribution to data:

• Parametric methods based on maximum likelihood estimation (MLE).
• Nonparametric methods like empirical cumulative distribution function (ECDF).
• Kernel density estimation for different dimensions, as well as for directional data.

Testing goodness-of-fit:

• Kolmogorov-Smirnov test
• Normal plots.
• A slew of tests for gaussianity of data.
• Kuiper's test and other similar tests for directional data.

Regression:

• Ordinary least squares
• Multiple regression
• Nonparametric regression, like LOESS
• Robust regression, using M-estimation and Least Trimmed Squares (LTS)

Multivariate techniques:

• Principal Component Analysis (PCA)
• Canonical correlation

Transforming data:

• Applying a formula
• Selecting a subset

Standard statistical tests:

• Parametric tests like t-test and Z-test
• Nonparametric tests like Wilcoxon's rank sum test and Kolmogorov-Smirnov test.

VOStat uses different output formats for different purposes:

• graphical output: png, eps and pdf.
• tabular output: VO table (downloadable by [right/command]-clicking or via SAMP)
• R scripts: ASCII text, that you can copy-n-paste from the webpage.
• R workspace: Binary R format.

samp.app.ping
samp.hub.disconnnect
samp.hub.event.metadata
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samp.hub.event.subscriptions
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client.env.get
table.load.votable