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- _a_v_a_s: _A_d_d_i_t_i_v_i_t_y _a_n_d _v_a_r_i_a_n_c_e _s_t_a_b_i_l_i_z_a_t_i_o_n _f_o_r _r_e_g_r_e_s_s_i_o_n
-
- avas(x, y, wt, mon, lin, cat, circ, delrsq,yspan)
-
- _A_r_g_u_m_e_n_t_s:
-
- x:
- a matrix containing the independent variables.
-
- y:
- a vector containing the response variable.
-
- wt:
- an optional vector of weights.
-
- mon:
- an optional integer vector specifying which variables
- are to be transformed by monotone transformations.
- Positive values in mon refer to columns of the x matrix
- and zero to the response variable.
-
- lin:
- an optional integer vector specifying which variables
- are to be transformed by linear transformations. Posi-
- tive values in lin refer to columns of the x matrix and
- zero to the response variable.
-
- cat:
- an optional integer vector specifying which variables
- assume categorical values. Positive values in cat
- refer to columns of the x matrix and zero to the
- response variable.
-
- circ:
- an integer vector specifying which variables assume
- circular (periodic) values. Positive values in circ
- refer to columns of the x matrix and zero to the
- response variable.
-
- delrsq:
- termination threshold. Iteration stops when R-squared
- changes by less than delrsq in 3 consecutive iterations
- (default 0.01).
-
- yspan:
- Optional window size parameter for smoothing the vari-
- ance. Range[0,1]. Default=0 (cross validated choice).
- .5 is a reasonable alternative to try.
-
- Value:
-
- structure with the following components:
-
- x:
- the input x matrix.
-
- y:
- the input y vector.
-
- tx:
- the transformed x values.
-
- ty:
- the transformed y values.
-
- rsq:
- the multiple R-squared value for the transformed values.
-
- l:
- not used in this version of avas
-
- m:
- not used in this version of avas
-
- yspan:
- span used for smoothing the variance
-
- iters:
- iteration number and rsq for that iteration
-
- niters:
- number of iterations used
-
- Rob Tibshirani, "Estimating optimal transformations for
- regression". JASA Vol 83, No 402 Page 394 Version: Mar
- 18/1987
-
- _E_x_a_m_p_l_e_s:
-
- TWOPI <- 8*atan(1)
- x <- runif(200,0,TWOPI)
- y <- exp(sin(x)+rnorm(200)/2)
- a <- avas(x,y)
- plot(a,ay) # view the response transformation
- plot(a,ax) # view the carrier transformation
- plot(ax,ay) # examine the linearity of the fitted model
-
-