Variable Transformations

Variance Stabilizing Transformations

Figure 32.13 shows the transformations that are available when you select Variance stabilizing from the Family list. Variance stabilizing transformations are often used to transform a variable whose variance depends on the value of the variable. For example, the variability of a variable y might increase as y increases. Equations for these transformations are given in Table 32.3.

ugtransformvarstab.png (9377 bytes)

Figure 32.13: Variance Stabilizing Transformations


Table 32.3: Description of Variance Stabilizing Transformations
  Default Name of  
Transformation Parameter New Variable Equation
log(Y+a) a=0 Log_Y \log(y+a), y+a\gt
log10(Y+a) a=0 Log10_Y \log_{10}(y+a), y+a\gt
sqrt(Y+a) a=0 Sqrt_Y \sqrt{y+a}, y+a\gt
1 / Y   Inv_Y  1/y, y\neq 0
arcsinh(Y)   Arcsinh_Y \log(y+\sqrt{y^2+1})
generalized log(Y;a) a=0 GLog_Y \log((y+\sqrt{y^2+a^2})/2)
log-linear hybrid(Y;a) a=1 LogLin_Y See text.

The log-linear hybrid transformation is defined for a\gt as follows:

h(y;a) = \{ y/a + \log(a)-1 & {if } y\lt a \ \log y & {if } y \geq a .
The function is linear for y\lt a, logarithmic for y\gt a, and continuously differentiable.

The generalized log and the log-linear hybrid transformations were introduced in the context of gene-expression microarray data by Rocke and Durbin (2003).

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