≡ START Guide Deutsch Adjustment : Adjustment with observation equations

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Functional and stochastic adjustment model Constraints (restrictions) for parameters Functions of adjusted quantities In the library
The general adjustment problem with observation equations is solved in the least squares sense, optionally with constraints for parameters and functions of adjusted quantities.

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Note

Probability of type I decision error

≡ START Guide Deutsch Functional and stochastic adjustment model

Solve l+v=Ax in the least squares sense: vTPv→min.

n-vector l n names of observations u names of parameters

≡ START Guide Deutsch Constraints (restrictions) for parameters

Optionally you may here specify m linear(ized) constraints BT x=b , which are fulfilled by the true parameters x and should also be fulfilled by the adjusted parameters x .

m-Vektor b

≡ START Guide Deutsch Functions of adjusted quantities

Optionally you may here specify k linear(ized) functions of adjusted parameters f = F x or of adjusted observations f = F l for which values and standard deviations are desired.

k names of functions

Check the matrix condition of matrices to be inverted lightbulb

1 more example

Did you know? Many or all observations, weights, standard deviations and names may be written in one row, only the succession and count must match the corresponding matrices.

≡ START Guide Deutsch In the library

Link Author(s)Title Year Type Pages
MByte
PDF: open accessHalsig S, Ernst A, Schuh WDAusgleichung von Höhennetzen aus mehreren Epochen unter Berücksichtigung von Bodenbewegungen2013BasR9
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PDF: open accessBezirksregierung KölnAusgleichung im Liegenschaftskataster2009Offi98
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PDF: open accessBoysen ABeurteilung von Softwarepaketen zur Ausgleichungsrechnung2009Thes120
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PDF: open accessNeitzel F, Petrovic STotal Least Squares (TLS) im Kontext der Ausgleichung nach kleinsten Quadraten am Beispiel der ausgleichenden Geraden2008BasR11
0.1