- Aït-Sahalia Y (1999) Transition densities for interest rate and other nonlinear diffusions. J Financ 54(4):1361–1395.
Paper not yet in RePEc: Add citation now
- Aït-Sahalia Y (2002) Maximum likelihood estimation of discretely sampled diffusions: a closed-form approximation approach. Econometrica 70(1):223–262.
Paper not yet in RePEc: Add citation now
- Aït-Sahalia Y (2008) Closed-form likelihood expansions for multivariate diffusions. Ann Stat 36(2):906–937.
Paper not yet in RePEc: Add citation now
Aït-Sahalia Y, Kimmel R (2007) Maximum likelihood estimation of stochastic volatility models. J Financ Econ 83(2):413–452.
Bakshi G, Ju N (2005) A refinement to Aït-Sahalia’s (2002) Maximum likelihood estimation of discretely sampled diffusions: a closed-form approximation approach. J Bus 78(5):2037–2052.
- Baltazar-Larios F, Sørensen M (2010) Maximum likelihood estimation for integrated diffusion processes. Contemporary quantitative finance. Springer, Berlin, pp 407–423.
Paper not yet in RePEc: Add citation now
Bertail P, Clémençon S (2008) Approximate regenerative-block bootstrap for Markov chains. Comput Stat Data Anal 52(5):2739–2756.
Beskos A, Papaspiliopoulos O, Roberts GO, Fearnhead P (2006) Exact and computationally efficient likelihood-based estimation for discretely observed diffusion processes (with discussion). J R Stat Soc Ser B (Stat Methodol) 68(3):333–382.
- Boyd JP (2018) Dynamics of the equatorial ocean. Springer, Berlin.
Paper not yet in RePEc: Add citation now
Brandt MW, Santa-Clara P (2002) Simulated likelihood estimation of diffusions with an application to exchange rate dynamics in incomplete markets. J Financ Econ 63(2):161–210.
- Brunel E, Comte F, Lacour C (2007) Adaptive estimation of the conditional density in the presence of censoring. Sankhyā Indian J Stat 69:734–763.
Paper not yet in RePEc: Add citation now
Choi S (2015) Explicit form of approximate transition probability density functions of diffusion processes. J Econom 187(1):57–73.
- Dacunha-Castelle D, Duflo M (1982) Probabilités et statistiques: problèmes à temps fixe, vol 1. Masson.
Paper not yet in RePEc: Add citation now
- Dedecker J, Samson A, Taupin M-L (2014) Estimation in autoregressive model with measurement error. ESAIM Prob Stat 18:277–307.
Paper not yet in RePEc: Add citation now
- Doukhan P (1994) Mixing. volume 85 of Lecture notes in statistics. Springer, New York (Properties and examples).
Paper not yet in RePEc: Add citation now
Egorov AV, Li H, Xu Y (2003) Maximum likelihood estimation of time-inhomogeneous diffusions. J Econom 114(1):107–139.
El Kolei S, Pelgrin F (2017) Parametric inference of autoregressive heteroscedastic models with errors in variables. Stat Prob Lett 130:63–70.
- Favetto B (2014) Parameter estimation by contrast minimization for noisy observations of a diffusion process. Statistics 48(6):1344–1370.
Paper not yet in RePEc: Add citation now
- Favetto B (2016) Estimating functions for noisy observations of ergodic diffusions. Stat Infer Stoch Process 19(1):1–28.
Paper not yet in RePEc: Add citation now
- Florens-Zmirou D (1989) Approximate discrete-time schemes for statistics of diffusion processes. Stat J Theor Appl Stat 20(4):547–557.
Paper not yet in RePEc: Add citation now
- Genon-Catalot V, Jacod J (1993) On the estimation of the diffusion coefficient for multi-dimensional diffusion processes. Annales de l’IHP Probabilités et statistiques 29:119–151.
Paper not yet in RePEc: Add citation now
- Genon-Catalot V, Jeantheau T, Laredo C (1999) Parameter estimation for discretely observed stochastic volatility models. Bernoulli 5(5):855–872.
Paper not yet in RePEc: Add citation now
- Genon-Catalot V, Jeantheau T, Larédo C (2000) Stochastic volatility models as hidden Markov models and statistical applications. Bernoulli 6(6):1051–1079.
Paper not yet in RePEc: Add citation now
Gloter A (2006) Parameter estimation for a discretely observed integrated diffusion process. Scand J Stat 33(1):83–104.
Hansen LP, Scheinkman JA, Touzi N (1998) Spectral methods for identifying scalar diffusions. J Econom 86(1):1–32.
- Honoré P (1997) Maximum likelihood estimation of non-linear continuous-time term-structure models. Available at SSRN 7669.
Paper not yet in RePEc: Add citation now
- Hurn A, Jeisman J, Lindsay K (2005) ML estimation of the parameters of sde’s by numerical solution of the Fokker–Planck equation. In: MODSIM 2005: international congress on modelling and simulation: advances and applications for management and decision making, pp 849–855. Citeseer.
Paper not yet in RePEc: Add citation now
- Jensen B, Poulsen R (2002) Transition densities of diffusion processes: numerical comparison of approximation techniques. J Derivat 9(4):18–32.
Paper not yet in RePEc: Add citation now
- Kessler M (1997) Estimation of an ergodic diffusion from discrete observations. Scand J Stat 24(2):211–229.
Paper not yet in RePEc: Add citation now
Kessler M (2000) Simple and explicit estimating functions for a discretely observed diffusion process. Scand J Stat 27(1):65–82.
- Kessler M, Lindner A, Sorensen M (2012) Statistical methods for stochastic differential equations. Chapman and Hall/CRC, Boca Raton.
Paper not yet in RePEc: Add citation now
- Lacour C (2007) Adaptive estimation of the transition density of a Markov chain. Annales de l’IHP Probabilités et statistiques 43:571–597.
Paper not yet in RePEc: Add citation now
Lacour C (2008) Adaptive estimation of the transition density of a particular hidden Markov chain. J Multivar Anal 99(5):787–814.
- Lacour C (2008) Least squares type estimation of the transition density of a particular hidden Markov chain. Electron J Stat 2:1–39.
Paper not yet in RePEc: Add citation now
Lacour C (2008) Nonparametric estimation of the stationary density and the transition density of a Markov chain. Stoch Process Appl 118(2):232–260.
Lee YD, Song S, Lee E-K (2014) The delta expansion for the transition density of diffusion models. J Econom 178:694–705.
- Li C (2013) Maximum-likelihood estimation for diffusion processes via closed-form density expansions. Ann Stat 41(3):1350–1380.
Paper not yet in RePEc: Add citation now
Lo AW (1988) Maximum likelihood estimation of generalized Itô processes with discretely sampled data. Econom Theor 4(2):231–247.
- Pedersen AR (1995) A new approach to maximum likelihood estimation for stochastic differential equations based on discrete observations. Scand J Stat 22:55–71.
Paper not yet in RePEc: Add citation now
- Pedersen AR (1995) Consistency and asymptotic normality of an approximate maximum likelihood estimator for discretely observed diffusion processes. Bernoulli 1:257–279.
Paper not yet in RePEc: Add citation now
Picchini U, Samson A (2018) Coupling stochastic EM and approximate Bayesian computation for parameter inference in state-space models. Comput Stat 33(1):179–212.
- Rogers L (1982) Stochastic differential equations and diffusion processes: Nobuyuki Ikeda and Shinzo Watanabe. North-Holland, Amsterdam, 1981, xiv+ 464 pp, dfl. 175.00. Rogers L, Williams D, Diffusions, Markov processes and martingales, vol 2, 2 ed. Cambridge Mathematical Library, Cambridge University Press.
Paper not yet in RePEc: Add citation now
- Särkkä S, Hartikainen J, Mbalawata IS, Haario H (2015) Posterior inference on parameters of stochastic differential equations via non-linear gaussian filtering and adaptive MCMC. Stat Comput 25(2):427–437.
Paper not yet in RePEc: Add citation now
Sermaidis G, Papaspiliopoulos O, Roberts GO, Beskos A, Fearnhead P (2013) Markov chain Monte Carlo for exact inference for diffusions. Scand J Stat 40(2):294–321.
Singer H (2006) Moment equations and Hermite expansion for nonlinear stochastic differential equations with application to stock price models. Comput Stat 21(3–4):385–397.
- Sørensen M (2009) Parametric inference for discretely sampled stochastic differential equations. Springer, Berlin, Heidelberg, pp 531–553.
Paper not yet in RePEc: Add citation now
- Stramer O, Yan J (2007) On simulated likelihood of discretely observed diffusion processes and comparison to closed-form approximation. J Comput Graph Stat 16(3):672–691.
Paper not yet in RePEc: Add citation now
- Von Neumann J (1941) Distribution of the ratio of the mean square successive difference to the variance. Ann Math Stat 12(4):367–395.
Paper not yet in RePEc: Add citation now
- Wong E (1964) The construction of a class of stationary Markoff processes. Stoch Process Math Phys Eng 17:264–276.
Paper not yet in RePEc: Add citation now
Yoshida N (1992) Estimation for diffusion processes from discrete observation. J Multivar Anal 41(2):220–242.