Update forecast2.R

It supposed that Yeo-Johnson modification of BoxCox transformation is better than original BoxCox power transformation in case when one have a data with mixed negative, positive values. I have tested it with linear regression prediction of "forecast" package and it produces more reliable confidence levels than BoxCox transformation does. It also solves "NA" values problem of BoxCox transformation. Please see "A New Family of Power Transformations to Improve Normality or Symmetry", In-Kwon Yeo and Richard A. Johnson, Biometrika, Vol. 87, No. 4 (Dec., 2000), pp. 954-959