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Linear programming-based estimators in simple linear regression. (2011). Preve, Daniel ; Medeiros, Marcelo.
In: Journal of Econometrics.
RePEc:eee:econom:v:165:y:2011:i:1:p:128-136.

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  1. Linear programming-based estimators in nonnegative autoregression. (2015). Preve, Daniel.
    In: Journal of Banking & Finance.
    RePEc:eee:jbfina:v:61:y:2015:i:s2:p:s225-s234.

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  2. A simple and general approach to fitting the discount curve under no-arbitrage constraints. (2015). Fengler, Matthias ; Hin, Lin-Yee.
    In: Finance Research Letters.
    RePEc:eee:finlet:v:15:y:2015:i:c:p:78-84.

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  3. A simple and general approach to fitting the discount curve under no-arbitrage constraints. (2014). Fengler, Matthias ; Hin, Lin-Yee.
    In: Economics Working Paper Series.
    RePEc:usg:econwp:2014:23.

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References

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  1. Curtiss, J.H. On the distribution of the quotient of two chance variables. 1941 The Annals of Mathematical Statistics. 12 409-421
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  2. Datta, S. ; Mathew, G. ; McCormick, W.P. Nonlinear autoregression with positive innovations. 1998 Australian & New Zealand Journal of Statistics. 40 229-239
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  3. Datta, S. ; McCormick, W.P. Bootstrap inference for a first-order autoregression with positive innovations. 1995 Journal of the American Statistical Association. 90 1289-1300
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  4. Davis, R.A. ; McCormick, W.P. Estimation for first-order autoregressive processes with positive or bounded innovations. 1989 Stochastic Processes and their Applications. 31 237-250

  5. Feigin, P.D. ; Kratz, M.F. ; Resnick, S.I. Parameter estimation for moving averages with positive innovations. 1996 The Annals of Applied Probability. 12 1157-1190
    Paper not yet in RePEc: Add citation now
  6. Feigin, P.D. ; Resnick, S.I. Limit distributions for linear programming time series estimators. 1994 Stochastic Processes and their Applications. 51 135-165

  7. Nielsen, B. ; Shephard, N. Likelihood analysis of a first-order autoregressive model with exponential innovations. 2003 Journal of Time Series Analysis. 24 337-344

  8. Preve, D., 2011. Linear programming-based estimators in nonnegative autoregression. Manuscript.
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Cocites

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  1. How to verify that a given process is a L\evy-Driven Ornstein-Uhlenbeck Process. (2025). Abdelrazeq, Ibrahim ; Zhanbyrshy, Dinmukhammed ; Smith, Hardy.
    In: Papers.
    RePEc:arx:papers:2501.03434.

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  2. Forecasting Realized Volatility Using a Nonnegative Semiparametric Model. (2019). Yu, Jun ; Preve, Daniel ; Eriksson, Anders ; JunYu, ; Daniel, .
    In: JRFM.
    RePEc:gam:jjrfmx:v:12:y:2019:i:3:p:139-:d:262198.

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  3. Using degradation-with-jump measures to estimate life characteristics of lithium-ion battery. (2019). Liu, Hao ; Feng, Qianmei ; Shu, Yin.
    In: Reliability Engineering and System Safety.
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  4. Nonparametric intermediate order regression quantiles. (2019). Otsu, Taisuke ; Ichimura, Hidehiko ; Altonji, Joseph .
    In: STICERD - Econometrics Paper Series.
    RePEc:cep:stiecm:608.

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  5. Linear programming-based estimators in nonnegative autoregression. (2015). Preve, Daniel.
    In: Journal of Banking & Finance.
    RePEc:eee:jbfina:v:61:y:2015:i:s2:p:s225-s234.

    Full description at Econpapers || Download paper

  6. Predictor Selection for Positive Autoregressive Processes. (2014). Yang, Chiao-Yi ; Ing, Ching-Kang .
    In: Journal of the American Statistical Association.
    RePEc:taf:jnlasa:v:109:y:2014:i:505:p:243-253.

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  7. .

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  8. Spectral estimates for high-frequency sampled continuous-time autoregressive moving average processes. (2013). Fuchs, Florian ; Fasen, Vicky .
    In: Journal of Time Series Analysis.
    RePEc:bla:jtsera:v:34:y:2013:i:5:p:532-551.

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  9. Inference for extremal conditional quantile models, with an application to market and birthweight risks. (2011). Fernandez-Val, Ivan ; Chernozhukov, Victor.
    In: CeMMAP working papers.
    RePEc:ifs:cemmap:40/11.

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  10. Parameter estimation for first-order bifurcating autoregressive processes with Weibull innovations. (2011). Zhang, Chenhua .
    In: Statistics & Probability Letters.
    RePEc:eee:stapro:v:81:y:2011:i:12:p:1961-1969.

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  11. Linear programming-based estimators in simple linear regression. (2011). Preve, Daniel ; Medeiros, Marcelo.
    In: Journal of Econometrics.
    RePEc:eee:econom:v:165:y:2011:i:1:p:128-136.

    Full description at Econpapers || Download paper

  12. Testing the tail index in autoregressive models. (2009). Picek, Jan ; Jurekova, Jana ; Koul, Hira .
    In: Annals of the Institute of Statistical Mathematics.
    RePEc:spr:aistmt:v:61:y:2009:i:3:p:579-598.

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  13. Forecasting Realized Volatility Using A Nonnegative Semiparametric Model. (2009). Yu, Jun ; Preve, Daniel ; Eriksson, Anders.
    In: Working Papers.
    RePEc:siu:wpaper:22-2009.

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  14. Maximum Likelihood Estimation for a First‐Order Bifurcating Autoregressive Process with Exponential Errors. (2005). Zhou, J. ; Basawa, I. V..
    In: Journal of Time Series Analysis.
    RePEc:bla:jtsera:v:26:y:2005:i:6:p:825-842.

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  15. Extremal quantile regression. (2005). Chernozhukov, Victor.
    In: Papers.
    RePEc:arx:papers:math/0505639.

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  16. Bayesian prediction in threshold autoregressive models with exponential white noise. (2004). Pereira, Isabel ; Amaral-Turkman, Antonia M..
    In: TEST: An Official Journal of the Spanish Society of Statistics and Operations Research.
    RePEc:spr:testjl:v:13:y:2004:i:1:p:45-64.

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  17. Asymptotic theory for M-estimators of boundaries. (2003). Knight, Keith.
    In: SFB 373 Discussion Papers.
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  18. Estimation of the index parameter for autoregressive data using the estimated innovations. (1999). Allen, Michael R. ; Datta, Somnath.
    In: Statistics & Probability Letters.
    RePEc:eee:stapro:v:41:y:1999:i:3:p:315-324.

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  19. Estimation for a class of positive nonlinear time series models. (1996). Pallant, Diana L. ; Brown, Tim C. ; Feigin, Paul D..
    In: Stochastic Processes and their Applications.
    RePEc:eee:spapps:v:63:y:1996:i:2:p:139-152.

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  20. .

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