Trendtool: Difference between revisions

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===Purpose===
===Purpose===
Univariate trend analysis tool.
Univariate trend analysis tool.
===Synopsis===
===Synopsis===
:trendtool(axis,data)
:trendtool(axis,data)
:trendtool(data)
:trendtool(data)
:trendtool
:trendtool
===Description===
===Description===
TRENDTOOL allows the user to graphically perform univariate analysis of two-way data. Inputs are axis which is the variable scale to plot against [can be omitted] and data the data to plot in which rows are samples. If data is omitted, the user is prompted to load a dataset to analyze.
TRENDTOOL allows the user to graphically perform univariate analysis of two-way data. Inputs are axis which is the variable scale to plot against [can be omitted] and data the data to plot in which rows are samples. If data is omitted, the user is prompted to load a dataset to analyze.
Right-clicking on the trend data plot allows placement of "markers". Markers return either the height at a point or integrated area between two points. Reference markers can be added to each marker to subtract the height at a point or subtract a two-point baseline from the associated marker. Markers can be saved or loaded using the toolbar buttons. A Waterfall plot (linked to axis range shown in data plot) can be created using the waterfall toolbar button.  
Right-clicking on the trend data plot allows placement of "markers". Markers return either the height at a point or integrated area between two points. Reference markers can be added to each marker to subtract the height at a point or subtract a two-point baseline from the associated marker. Markers can be saved or loaded using the toolbar buttons. A Waterfall plot (linked to axis range shown in data plot) can be created using the waterfall toolbar button.  
The results of the analysis are plotted in the trend results plot which shows a color-coded results of the univariate analysis and allows saving of the analysis results and selection of points to show in the trend data figure.
The results of the analysis are plotted in the trend results plot which shows a color-coded results of the univariate analysis and allows saving of the analysis results and selection of points to show in the trend data figure.
===See Also===
===See Also===
[[pca]], [[plotgui]]
[[pca]], [[plotgui]]
'''tsqlim'''
'''tsqlim'''
===Purpose===
===Purpose===
Calculates PCA confidence limits for Hotelling's T<sup>2</sup>.
Calculates PCA confidence limits for Hotelling's T<sup>2</sup>.
===Synopsis===
===Synopsis===
:tsqcl = tsqlim(m,pc,cl)
:tsqcl = tsqlim(m,pc,cl)
:tsqcl = tsqlim(model,cl)
:tsqcl = tsqlim(model,cl)
===Description===
===Description===
Inputs can be in one of two forms:
Inputs can be in one of two forms:
(a) the number of samples m, the number of principal components used pc, and the fractional confidence limit, cl (0 < cl < 1) which can be a scalar or a vector (to calculate multiple confidence limits simultaneously).
(a) the number of samples m, the number of principal components used pc, and the fractional confidence limit, cl (0 < cl < 1) which can be a scalar or a vector (to calculate multiple confidence limits simultaneously).
or (b) a standard model structure, model, and the fractional confidence limit, cl (0 < cl < 1).
or (b) a standard model structure, model, and the fractional confidence limit, cl (0 < cl < 1).
The output tsqcl is the confidence limit. See Jackson (1991).
The output tsqcl is the confidence limit. See Jackson (1991).
===Examples===
===Examples===
:tsqcl = tsqlim(15,2,0.95)
:tsqcl = tsqlim(15,2,0.95)
:model = pca(data,pc); tsqcl = tsqlim(model,0.95)
:model = pca(data,pc); tsqcl = tsqlim(model,0.95)
===See Also===
===See Also===
[[analysis]], [[pca]], [[pcr]], [[pls]]
[[analysis]], [[pca]], [[pcr]], [[pls]]

Revision as of 15:27, 3 September 2008

Purpose

Univariate trend analysis tool.

Synopsis

trendtool(axis,data)
trendtool(data)
trendtool

Description

TRENDTOOL allows the user to graphically perform univariate analysis of two-way data. Inputs are axis which is the variable scale to plot against [can be omitted] and data the data to plot in which rows are samples. If data is omitted, the user is prompted to load a dataset to analyze.

Right-clicking on the trend data plot allows placement of "markers". Markers return either the height at a point or integrated area between two points. Reference markers can be added to each marker to subtract the height at a point or subtract a two-point baseline from the associated marker. Markers can be saved or loaded using the toolbar buttons. A Waterfall plot (linked to axis range shown in data plot) can be created using the waterfall toolbar button.

The results of the analysis are plotted in the trend results plot which shows a color-coded results of the univariate analysis and allows saving of the analysis results and selection of points to show in the trend data figure.

See Also

pca, plotgui

tsqlim

Purpose

Calculates PCA confidence limits for Hotelling's T2.

Synopsis

tsqcl = tsqlim(m,pc,cl)
tsqcl = tsqlim(model,cl)

Description

Inputs can be in one of two forms:

(a) the number of samples m, the number of principal components used pc, and the fractional confidence limit, cl (0 < cl < 1) which can be a scalar or a vector (to calculate multiple confidence limits simultaneously).

or (b) a standard model structure, model, and the fractional confidence limit, cl (0 < cl < 1).

The output tsqcl is the confidence limit. See Jackson (1991).

Examples

tsqcl = tsqlim(15,2,0.95)
model = pca(data,pc); tsqcl = tsqlim(model,0.95)

See Also

analysis, pca, pcr, pls