| Preface | p. v |
| Introduction | p. 1 |
| Estimation of a density | p. 2 |
| Estimation of a regression curve | p. 10 |
| Estimation of functionals of processes | p. 14 |
| Content of the book | p. 19 |
| Kernel estimator of a density | p. 23 |
| Introduction | p. 23 |
| Risks and optimal bandwidths for the kernel estimator | p. 25 |
| Weak convergence | p. 29 |
| Minimax and histogram estimators | p. 33 |
| Estimation of functionals of a density | p. 34 |
| Density of absolutely continuous distributions | p. 37 |
| Hellinger distance between a density and its estimator | p. 39 |
| Estimation of the density under right-censoring | p. 40 |
| Estimation of the density of left-censored variables | p. 42 |
| Kernel estimator for the density of a process | p. 44 |
| Exercises | p. 46 |
| Kernel estimator of a regression function | p. 49 |
| Introduction and notation | p. 49 |
| Risks and convergence rates for the estimator | p. 50 |
| Optimal bandwidths | p. 56 |
| Weak convergence of the estimator | p. 60 |
| Estimation of a regression curve by local polynomials | p. 62 |
| Estimation in regression models with functional variance | p. 64 |
| Estimation of the mode of a regression function | p. 68 |
| Estimation of a regression function under censoring | p. 69 |
| Proportional odds model | p. 70 |
| Estimation for the regression function of processes | p. 71 |
| Exercises | p. 73 |
| Limits for the varying bandwidths estimators | p. 75 |
| Introduction | p. 75 |
| Estimation of densities | p. 76 |
| Estimation of regression functions | p. 81 |
| Estimation for processes | p. 84 |
| Exercises | p. 85 |
| Nonparametric estimation of quantiles | p. 87 |
| Introduction | p. 87 |
| Asymptotics for the quantile processes | p. 89 |
| Bandwidth selection | p. 95 |
| Estimation of the conditional density of Y given X | p. 98 |
| Estimation of conditional quantiles for processes | p. 100 |
| Inverse of a regression function | p. 102 |
| Quantile function of right-censored variables | p. 104 |
| Conditional quantiles with variable bandwidth | p. 105 |
| Exercises | p. 106 |
| Nonparametric estimation of intensities for stochastic processes | p. 107 |
| Introduction | p. 107 |
| Risks and convergences for estimators of the intensity | p. 110 |
| Kernel estimator of the intensity | p. 111 |
| Histogram estimator of the intensity | p. 116 |
| Risks and convergences for multiplicative intensities | p. 118 |
| Models with nonparametric regression functions | p. 119 |
| Models with parametric regression functions | p. 120 |
| Histograms for intensity and regression functions | p. 124 |
| Estimation of the density of duration excess | p. 126 |
| Estimators for processes on increasing intervals | p. 130 |
| Models with varying intensity or regression coefficients | p. 132 |
| Progressive censoring of a random time sequence | p. 135 |
| Exercises | p. 136 |
| Estimation in semi-parametric regression models | p. 137 |
| Introduction | p. 137 |
| Convergence of the estimators | p. 139 |
| Nonparametric regression with a change of variables | p. 143 |
| Exercises | p. 146 |
| Diffusion processes | p. 147 |
| Introduction | p. 147 |
| Estimation for continuous diffusions by discretization | p. 149 |
| Estimation for continuous diffusion processes | p. 154 |
| Estimation of discretely observed diffusions with jumps | p. 158 |
| Continuous estimation for diffusions with jumps | p. 162 |
| Transformations of a non-stationary Gaussian process | p. 164 |
| Exercises | p. 166 |
| Applications to time series | p. 167 |
| Nonparametric estimation of the mean | p. 168 |
| Periodic models for time series | p. 171 |
| Nonparametric estimation of the covariance function | p. 172 |
| Nonparametric transformations for stationarity | p. 174 |
| Change-points in time series | p. 174 |
| Exercises | p. 181 |
| Appendices | p. 183 |
| Appendix A | p. 183 |
| Appendix B | p. 184 |
| Appendix C | p. 184 |
| Appendix D | p. 187 |
| Notations | p. 189 |
| Bibliography | p. 191 |
| Index | p. 197 |
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