CM Box User GuideMain Page | About | Special pages | Log in

Printable version | Disclaimer | Privacy policy | Current revision

(Difference between revisions)

Revision as of 12:39, 15 September 2006
Peter (Talk | contribs)
(Finding the relevant parameters with a principle component analysis)
← Previous diff
Revision as of 12:39, 15 September 2006
Peter (Talk | contribs)
(Step1. Finding the relevant parameters with a principle component analysis)
Next diff →
Line 21: Line 21:
<br> <br>
===Step1. Finding the relevant parameters with a principle component analysis=== ===Step1. Finding the relevant parameters with a principle component analysis===
-<br><br>+<br>
{|"class=prettytable" cellpadding="15" border="1" style="border-collapse:collapse" {|"class=prettytable" cellpadding="15" border="1" style="border-collapse:collapse"

Revision as of 12:39, 15 September 2006

Calibrating Yield

The yield function is a statistically derived function relating the water balance parameters (which constitute the outputs of the water balance model) and the other factors (farm inputs, trend) or NDVI with station yield. Once this function has been established, it can be used for early crop yield forecasting.

Although many different equations are possible, the most widely used one is the outcome of a multiple linear regression procedure:

Y = a + b1X1 + b2X2 + b3X3

where b1 to b3 are the corresponding X coefficients.

Using an example for Malawi, first it will be established which water balance parameters are good predictors for yield. Then the multiple linear regression will be performed.

The input data file for Malawi contains multiple lines for stations and years. In every line, besides yield, all possibly relevant water balance output parameters are stored. The file can be downloaded here


Step1. Finding the relevant parameters with a principle component analysis


Activate the Tools - Principle Component Analysis function. A settings window appears.
All parameters are selected.graph94.jpg
The output log file gives the most valuable results. The first, second and third component explains over 50% of te variance. The equation will be based on those 3 components.
Taking all parameters with correlation above 0.70 or below -0.70 the following list of regression parameters is obtained:
  • WRSIfin
  • DEFtot
  • DEFflow
  • DEFrip
  • ETAveg
  • ETArip
  • WEXTot
  • Xveg






Page generated in 0.355759 seconds.