Assuming that (Xt)t∈Z is a vector valued time series with a common
marginal distribution admitting a density f, our aim is to provide a wide
range of consistent estimators of f. We consider different methods of
estimation of the density as kernel, projection or wavelets ones. Various cases
of weakly dependent series are investigated including the Doukhan & Louhichi
(1999)'s η-weak dependence condition, and the ϕ~-dependence of
Dedecker & Prieur (2005). We thus obtain results for Markov chains, dynamical
systems, bilinear models, non causal Moving Average... From a moment inequality
of Doukhan & Louhichi (1999), we provide convergence rates of the term of error
for the estimation with the \L^q loss or almost surely, uniformly on compact
subsets