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2. Recursive nonparametric regression estimation for dependent strong mixing functional data. (2020). Slaoui, Yousri.
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3. A note on strong-consistency of componentwise ARH(1) predictors. (2019). Ruiz-Medina, M D ; Alvarez-Liebana, J.
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4. Strongly consistent autoregressive predictors in abstract Banach spaces. (2019). Ruiz-Medina, Maria D ; Alvarez-Liebana, Javier.
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   RePEc:eee:jmvana:v:170:y:2019:i:c:p:186-201.

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1. On projection methods for functional time series forecasting. (2022). Shang, Han Lin ; Jimenez, Raul ; Elias, Antonio.
   In: Journal of Multivariate Analysis.
   RePEc:eee:jmvana:v:189:y:2022:i:c:s0047259x21001688.

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2. Sparse semiparametric regression when predictors are mixture of functional and high-dimensional variables. (2021). Novo, Silvia ; Vieu, Philippe ; Aneiros, German.
   In: TEST: An Official Journal of the Spanish Society of Statistics and Operations Research.
   RePEc:spr:testjl:v:30:y:2021:i:2:d:10.1007_s11749-020-00728-w.

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3. Forecasting Australian subnational age-specific mortality rates. (2021). Shang, Han Lin ; Yang, Yang.
   In: Journal of Population Research.
   RePEc:spr:joprea:v:38:y:2021:i:1:d:10.1007_s12546-020-09250-0.

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4. Bandwidth selection for the Local Polynomial Double Conditional Smoothing under Spatial ARMA Errors*. (2021). Schafer, Bastian.
   In: Working Papers CIE.
   RePEc:pdn:ciepap:146.

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5. Recursive nonparametric regression estimation for dependent strong mixing functional data. (2020). Slaoui, Yousri.
   In: Statistical Inference for Stochastic Processes.
   RePEc:spr:sistpr:v:23:y:2020:i:3:d:10.1007_s11203-020-09223-3.

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6. Dynamical multiple regression in function spaces, under kernel regressors, with ARH(1) errors. (2019). Espejo, R M ; Ruiz-Medina, M D ; Miranda, D.
   In: TEST: An Official Journal of the Spanish Society of Statistics and Operations Research.
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7. Dynamic partially functional linear regression model. (2019). Zhang, Zhongzhan ; Du, Jiang ; Zhao, Hui.
   In: Statistical Methods & Applications.
   RePEc:spr:stmapp:v:28:y:2019:i:4:d:10.1007_s10260-019-00457-x.

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8. Composite quantile estimation in partial functional linear regression model with dependent errors. (2019). Zhang, Zhongzhan ; Zhu, Zhongyi ; Li, Ting ; Yu, Ping.
   In: Metrika: International Journal for Theoretical and Applied Statistics.
   RePEc:spr:metrik:v:82:y:2019:i:6:d:10.1007_s00184-018-0699-3.

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9. Tests for the linear hypothesis in semi-functional partial linear regression models. (2019). Zhu, Shuzhi ; Zhao, Peixin.
   In: Metrika: International Journal for Theoretical and Applied Statistics.
   RePEc:spr:metrik:v:82:y:2019:i:2:d:10.1007_s00184-018-0680-1.

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10. Semi-functional partially linear regression model with responses missing at random. (2019). Meng, Shuyu ; Kan, Rui ; Vieu, Philippe ; Ling, Nengxiang.
    In: Metrika: International Journal for Theoretical and Applied Statistics.
    RePEc:spr:metrik:v:82:y:2019:i:1:d:10.1007_s00184-018-0688-6.

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11. Intraday forecasts of a volatility index: functional time series methods with dynamic updating. (2019). Shang, Han Lin ; Kearney, Fearghal ; Yang, Yang.
    In: Annals of Operations Research.
    RePEc:spr:annopr:v:282:y:2019:i:1:d:10.1007_s10479-018-3108-4.

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12. A note on strong-consistency of componentwise ARH(1) predictors. (2019). Ruiz-Medina, M D ; Alvarez-Liebana, J.
    In: Statistics & Probability Letters.
    RePEc:eee:stapro:v:145:y:2019:i:c:p:224-228.

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13. Local polynomial estimation of regression operators from functional data with correlated errors. (2019). Su, Yingcai ; Benhenni, Karim ; Hassan, Ali Hajj.
    In: Journal of Multivariate Analysis.
    RePEc:eee:jmvana:v:170:y:2019:i:c:p:80-94.

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14. Estimation and testing for partially functional linear errors-in-variables models. (2019). Yu, Zhou ; Liu, Yanghui ; Zhang, Riquan ; Lian, Heng ; Zhu, Hanbing.
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    RePEc:eee:jmvana:v:170:y:2019:i:c:p:296-314.

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15. High-dimensional functional time series forecasting: An application to age-specific mortality rates. (2019). Shang, Han Lin ; Gao, Yuan ; Yang, Yanrong.
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    RePEc:eee:jmvana:v:170:y:2019:i:c:p:232-243.

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16. Quantifying prediction uncertainty for functional-and-scalar to functional autoregressive models under shape constraints. (2019). Rossini, Jacopo ; Canale, Antonio.
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17. Strongly consistent autoregressive predictors in abstract Banach spaces. (2019). Ruiz-Medina, Maria D ; Alvarez-Liebana, Javier.
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    RePEc:eee:jmvana:v:170:y:2019:i:c:p:186-201.

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18. Optimal rate for covariance operator estimators of functional autoregressive processes with random coefficients. (2019). Mourid, Tahar ; Allam, Abdelaziz.
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19. Parameter regimes in partial functional panel regression. (2019). Walders, Fabian ; Liebl, Dominik.
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20. Bootstrap in semi-functional partial linear regression under dependence. (2018). Vieu, Philippe ; Raa, Paula ; Vilar, Juan ; Aneiros, German.
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    RePEc:spr:testjl:v:27:y:2018:i:3:d:10.1007_s11749-017-0566-y.

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21. Semi-functional partial linear quantile regression. (2018). Lu, Zhiping ; Zhang, Riquan ; Ding, Hui.
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22. Some asymptotic theory for Silverman’s smoothed functional principal components in an abstract Hilbert space. (2017). Lakraj, Gamage Pemantha ; Ruymgaart, Frits .
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23. Asymptotic properties of a component-wise ARH(1) plug-in predictor. (2017). Ruiz-Medina, M D ; Alvarez-Liebana, J ; Bosq, D.
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25. Functional time series forecasting with dynamic updating: An application to intraday particulate matter concentration. (2017). Shang, Han Lin.
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26. Prediction Bands for Functional Data Based on Depth Measures. (2017). Jimenez, Raul Jose ; Fernandez, Antonio Elias.
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27. Varying coefficient partially functional linear regression models. (2016). Peng, Qing-Yan ; Tang, Nian-Sheng ; Zhou, Jian-Jun .
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28. Polynomial spline estimation for partial functional linear regression models. (2016). Chen, Zhao ; Peng, Qingyan ; Zhou, Jianjun.
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29. Efficiency in multivariate functional nonparametric models with autoregressive errors. (2016). Dabo-Niang, Sophie ; Guillas, S ; Ternynck, C.
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30. Gap between orthogonal projectors—Application to stationary processes. (2016). Viguier-Pla, Sylvie ; Boudou, Alain.
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31. Interaction models for functional regression. (2016). Usset, Joseph ; Maity, Arnab ; Staicu, Ana-Maria.
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32. Penalized function-on-function regression. (2015). Greven, Sonja ; Scheipl, Fabian ; Ivanescu, Andrada ; Staicu, Ana-Maria.
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33. Bayesian bandwidth estimation for a semi-functional partial linear regression model with unknown error density. (2014). Shang, Han Lin.
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34. A survey of functional principal component analysis. (2014). Shang, Han Lin.
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35. Estimation of the covariance matrix in multivariate partially linear models. (2014). Przystalski, Marcin.
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36. Partially linear modeling of conditional quantiles using penalized splines. (2014). Yu, Yan ; Wu, Chaojiang.
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37. Estimator selection and combination in scalar-on-function regression. (2014). Goldsmith, Jeff ; Scheipl, Fabian.
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38. Functional k-means inverse regression. (2014). Lin, Nan ; Wang, Guochang ; Zhang, Baoxue.
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39. Testing linearity in semi-parametric functional data analysis. (2013). Vieu, Philippe ; Aneiros-Perez, German .
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40. Nonparametric M-regression for functional ergodic data. (2013). Sekkal, Soumeya ; Laksaci, Ali ; Gheriballah, Abdelkader .
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41. Using Bagidis in nonparametric functional data analysis: Predicting from curves with sharp local features. (2013). von Sachs, Rainer ; Delsol, Laurent ; Timmermans, Catherine.
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42. A functional linear model for time series prediction with exogenous variables. (2012). Goia, Aldo.
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43. Spline estimators for semi-functional linear model. (2012). Chen, Min ; Zhou, Jianjun.
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44. Partially linear varying coefficient models stratified by a functional covariate. (2012). Huang, Jianhua Z. ; Maity, Arnab.
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45. On prediction rate in partial functional linear regression. (2012). Lee, Myung Hee ; Shin, Hyejin.
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46. Functional linear regression after spline transformation. (2012). Lin, Nan ; Wang, Guochang ; Zhang, Baoxue.
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47. Nonparametric time series forecasting with dynamic updating. (2011). Shang, Han Lin ; Hyndman, Rob ; Hyndman, Rob. J., .
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48. Using Bagidis in nonparametric functional data analysis: predicting from curves with sharp local features. (2011). von Sachs, Rainer ; Delsol, Laurent ; Timmermans, Catherine.
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49. Nonparametric modeling and forecasting electricity demand: an empirical study. (2010). Shang, Han Lin.
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50. Nonparametric time series forecasting with dynamic updating. (2009). Shang, Han Lin ; Hyndman, Rob.
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