This command performs quadrat covariance analysis on a contiguous data set.
Syntax
QuadCovar [options];
Menu Equivalent
Analysis→Contiguous Data→Quadrat Covariance Methods
Button Equivalent
Available Options
Method = BQC | SBQC | TTLQC | 3TLQC | PQC | RPQC | TQC | 2NLC | 3NLC | 4TLQC | 9TLQC | 5QC | 8TLQC | 27TLQC | 7QC
The Method parameter specifies the type of quadrat variance analysis to perform. 8TLQC, 27TLQC, and 7QC imply three-dimensional analysis and require the matrix specified by Data to be three-dimensional. 4TLQC, 9TLQC, and 5QC imply two-dimensional analysis, while the remaining methods all imply one-dimensional analysis. A method must be specified; there is no default.
Wrap = Yes | No
If Method refers to a one-dimensional analysis, this parameter controls whether the ends of the data transect will be wrapped or remain linear. The default is No.
MaxScale = Number
This specifies the maximum scale (as a percent of the size of the data matrix) over which to calculate the quadrat variance. This value can generally range from 0 to 50; certain analyses (3TLQC, TQC, 3NLC, 9TLQC, 5QC, 27TLQC , and 7QC) have an automatic cap of 33.3. The default is 10.
ScaleFactor = Number
This value is used to indicate the scale of the data quadrats. For example, if each quadrat is 10cm in size and you wish the results to be presented in meters, ScaleFactor should equal 0.1. On the other hand if you wish the results to be presented in cm, ScaleFactor should equal 10. It has no direct impact on the analysis; it only affects the units of the output. The default is 1.0.
Permute = Yes | No
Specifies whether a permutation test is being performed to set confidence intervals. Permutation parameters include Permutations and Interval.
Permutations = Number
When Permute = Yes, this controls the number of iterations that are being performed in the randomization test. The default is 999 (the minimum is 49).
Interval = Number
When Permute = Yes, specifies the width of the null distribution interval to be determined by the permutation test. The default is 0.95.
Save = Yes | No
Controls whether the output is saved into an independent matrix. The default is No.
SaveName = Name
When Save = Yes, this specifies the name of the output matrix. This name cannot be identical to the names of any other matrices already in memory.
Data = Name | #Number
Specifies the data matrices. They can be a rectangular or 3D data matrix. Data from Data1 will be contrasted with data from Data2. Data1 can be identical to Data2 if everything is contained within a single data matrix.
The following options apply when Data1 (or Data2) refers to a two-dimensional data matrix and Method refers to a one-dimensional analysis. In all cases, the parameters ending in 1 refer to the Data1 matrix and those ending in 2 to the Data2 matrix.
The following options apply when Data refers to a two-dimensional data matrix and Method refers to a one-dimensional analysis.
Columns1, Columns2 = All | None | {Name | #Number, Name | #Number, etc.}
For two-dimensional data matrices and one-dimensional analyses, this specifies which columns (if any) are to be analyzed by the specified Method. The default is to include all columns. Both Columns and Rows cannot be given a value of None.
Rows1, Rows2 = All | None | {Name | #Number, Name | #Number, etc.}
For two-dimensional data matrices and one-dimensional analyses, this specifies which rows (if any) are to be analyzed by the specified Method. The default is to include no rows. Both Columns and Rows cannot be given a value of None.
The following options apply when Data1 (or Data2) refers to a three-dimensional data matrix and Method refers to a one-dimensional analysis. In all cases, the parameters ending in 1 refer to the Data1 matrix and those ending in 2 to the Data2 matrix.
XCols1, XCols2 = All | None | {[Name | #Number, Name | #Number], [Name | #Number, Name | #Number], etc.}
YCols1, YCols2 = All | None | {[Name | #Number, Name | #Number], [Name | #Number, Name | #Number], etc.}
ZCols1, ZCols2 = All | None | {[Name | #Number, Name | #Number], [Name | #Number, Name | #Number], etc.}
For three-dimensional data matrices and one-dimensional analyses, these specify which columns are to be analyzed by the specified Method. Specific columns can be included within {}, listed as pairs enclosed by [], and, as usual can be identified by Name or #Number. Columns parallel to the x-axis are identified by the associated y- and z-variables; columns parallel to the y-axis are identified by the associated x- and z-variables, and columns parallel to the z-axis are identified by the associated x- and y-variables. XCols1, YCols1, and ZCols1 cannot all be given a value of None; neither can XCols2, YCols2, and ZCols2.
The following options apply when Data1 (or Data2) refers to a three-dimensional data matrix and Method refers to a two-dimensional analysis. In all cases, the parameters ending in 1 refer to the Data1 matrix and those ending in 2 to the Data2 matrix.
XYPlanes1, XYPlanes2 = All | None | {Name | #Number, Name | #Number, etc.}
XZPlanes1, XZPlanes2 = All | None | {Name | #Number, Name | #Number, etc.}
YZPlanes1, YZPlanes2 = All | None | {Name | #Number, Name | #Number, etc.}
For three-dimensional data matrices and two-dimensional analyses, these specify which planes are to be analyzed by the specified Method. Specific planes can be included within {} and listed by Name or #Number. XY planes are listed by the z-variable, XZ planes are listed by the y-variable, and YZ planes are listed by the x-variable. XYPlanes1, XZPlanes1, and YZPlanes1 cannot all be given a value of None.; neither can XYPlanes2, XZPlanes2, and YZPlanes2.