  The paper deals with the statistical analysis of several data sets associated
with shape invariant models with different translation, height and scaling
parameters. We propose to estimate these parameters together with the common
shape function. Our approach extends the recent work of Bercu and Fraysse to
multivariate shape invariant models. We propose a very efficient Robbins-Monro
procedure for the estimation of the translation parameters and we use these
estimates in order to evaluate scale parameters. The main pattern is estimated
by a weighted Nadaraya-Watson recursive estimator. We provide almost sure
convergence and asymptotic normality for all estimators. Finally, we illustrate
the convergence of our estimation procedure on simulated data as well as on
real ECG data.
