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Mathematical Statistics
Centre for Mathematical Sciences
Lund University with Lund Institute of Technology

Address: Box 118, SE-221 00 LUND, Sweden
Phone: +46 46 222 8550, Fax: +46 46 222 4623
Visitors address: Sölvegatan 18













  1. Rychlik, I.: Rainflow cycles, Markov chains and electrical circuits., NFMS-3187.
  2. Rychlik, I.: A note on Rice formula for intensity of level crossings of absolutely continuous processes. NFMS-3186.
  3. Lindoff, B. and Holst, J.: Suboptimal dual control of stochastic systems with time-varying parameters., TFSM-3141.
  4. Asmussen, S. and Kella, O.: A multi-dimensional martingale for Markov additive processes and its applications., NFMS-3185.
  5. Lindgren, G., Rychlik, I. and Prevosto, M.: Stochastic Doppler shift and encountered wave period distributions in Gaussian waves., TFMS-3140.
  6. Pettersson, R.: Numerical approximation of stochastic Sturm-Liouville and obstacle problems., TFMS-3139.
  7. Svensson, A. and Holst, J.: Optimal prediction of level-crossings in piecewise linear Gaussian processes with changing catastrophe level., TFMS-3138.
  8. Asmussen, S. and Kalashnikov, V.: Failure rates of regenerative systems with heavy tails., NFMS-3184.
  9. Asmussen, S. and O'Cinneide, C.A.: Phase-type representations for matrix-geometric and matrix-exponential steady-state., NFMS-3183.
  10. Leadbetter, M.R. and Rychlik, I.: Extremes and high level exceedances of stationary random fields for ocean structure reliability., NFMS-3182.
  11. Lindoff, B.: On the optimal choice of the forgetting factor in the recursive least squares estimator., TFMS-3137.
  12. Lindoff, B. and Holst, J.: Adaptive predictive control for time-varying stochastic systems., TFMS-3136.
  13. Johannesson, P.: Rainflow cycles for switching processes with Markov structure., TFMS-3135.
  14. Lindoff, B.: First inverse moment of a generalized quadratic form., TFMS-3134.
  15. Pettersson, R.: Projection scheme for stochastic differential equations with convex constraints., TFMS-3133.
  16. Asmussen, S., Schmidli, H. and Schmidt, V.: Tail probabilities for non-standard risk and queuing with subexponential jumps., NFMS-3181.
  17. Asmussen, S. and Rubinstein, R.Y.: Sensitivity analysis of insurance risk models via simulation., NFMS-3180.
  18. Seleznjev, O.: Sampling designs for linear approximation of a random process., TFMS-3132.
  19. Bickel, P., Ritov, Y. and Rydén, T.: Asymptotic normality of the maximum-likelihood estimator for general hidden Markov models., TFMS-3131.
  20. Lindgren, G., Rychlik, I. and Provosto, M.: The relation between wave length and wave period distributions in random Gaussian waves., TFMS-3130.


  1. Frigyesi, A. and Hössjer, O.: Kernel estimates of dimension spectra for multifractal measures., NFMS-3179.
  2. Zhao, H., von Heiroth, P., Holst, J. and Arvastson, L.: Modelling the fuel consumption in a CHP plant., TFMS-3129.
  3. Furrer, H., Michna, Z. and Weron, A.: Stable Lévy motion approximation in collective risk theory., NFMS-3178.
  4. Rydén, T. and Titterington, D.M.: Computational Bayesian analysis of hidden Markov models., TFMS-3128.
  5. Michna, Z.: Self-similar processes in collective risk theory., NFMS-3177.
  6. Debicki, K., Michna, Z. and Rolski, T.: On the supremum of Gaussian processes over infinite horizon., NFMS-3176.
  7. Asmussen, S. and Turova, T.S.: Stationarity properties of neural networks., NFMS-3175.
  8. Lindström, T., Holst, U. and Edner, H.: Robust local polynomial regression and statistical evaluation of DOAS measurements., TFMS-3127.
  9. Sköld, M.: Kernel regression in the presence of size-bias., NFMS-3174.
  10. Krishnamurthy, V. and Rydén, T.: Consistent estimation of linear and non-linear autoregressive models with Markov regime., TFMS-3126.
  11. Asmussen, S. and Binswanger, K.: Simulation of ruin probabilities for subexponential claims., NFMS-3173.
  12. Zetterqvist, L.: Statistics for chemistry students - How to make a statistic course usable by focusing on applications., NFMS-3172.
  13. Asmussen, S.: Subexponential asymptotics for stochastic processes: extremal behaviour, stationary distributions and first passage probabilities. NFMS--3171.
  14. Rydén, T.: Asymptotically efficient recursive estimation for incomplete data models using the observed information., TFMS--3125.
  15. Bäckman, P.L., Lanke, J., Barlow, L. and Andrén-Sandberg, Å.: Decreasing incidence of exocrine pancreatic cancer in Sweden. Manuscript.
  16. Ljungquist, B., Lanke, J., Berg, S., McClearn, G.E. and Pedersen, N.L.: The effect of genetic factors for longevity: a comparison of identical and fraternal twins in the Swedish Twin Registry. Manuscript.
  17. Lidfeldt, J., Lanke, J., Sundquist, J. and Lindholm, L.: Old patients with hypertension: a 25-year longitudinal study of a geographically defined population (Dalby), aged 67 at entry. Manuscript.
  18. Johannesson, P. and Lindgren, G.: Rainflow cycles for switching processes with Markov structure. ITM report 1996:4, October 1996.


  1. Pettersson, R.: Penalization schemes for reflecting stochastic differential equations., NFMS-3170.
  2. Rychlik, I.: Simulation of load sequences from rainflow matrices: Markov method., NFMS-3169.
  3. Asmussen, S. and Taksar, M.: Controlled diffusion models for optimal dividend pay-out., NFMS-3168.
  4. Asmussen, S. and Klüppelberg, C.: Stationary M/G/1 excursions in the presence of heavy tails., NFMS-3167.
  5. Asmussen, S.: A probabilistic look at the Wiener-Hopf equation., NFMS-3166.
  6. Stromberg, A.J., Hawkins, D.M. and Hössjer, O.: The least trimmed differences regression estimator and alternatives., NFMS-3165.
  7. Rydén, T.: On recursive estimation for hidden markov models., TFMS-3124.
  8. Overbeck, L. and Rydén, T.: Estimation in the Cox-Ingersoll-Ross model., TFMS-3123.
  9. Ruppert, D., Wand, M.P. Holst, U. and Hössjer, O.: Local polynomial variance function estimation., TFMS-3122.
  10. Rootzén, H. and Olsson, J.: On the influence of the prior distribution in image reconstruction., NFMS-3164.
  11. Pettersson, R.: Wong-Zakai approximations for multivalued stochastic differential equations., NFMS-3163.
  12. Pettersson, R.: Wong-Zakai approximations for reflecting stochastic differential equations., NFMS-3162.
  13. Bøhm, B. and Zhao, H.: On operational optimization of Danish district heating systems - with specific interest in optimum temperature level., TFMS-3121.
  14. Zhao, H. and Holst, J.: Optimum operation of district heating systems - approaches used in nordic countries., TFMS-3120.
  15. Zhao, H., Bøhm, B. and Ravn, H.F.: On optimum operation of a CHP type of district heating system by mathematical modelling., TFMS-3119.
  16. Lindoff, B. and Holst, J.: Bias and covariance of the RLS-estimator with exponential forgetting in vector autoregressions., TFMS-3118.
  17. Svensson, A., Holst, J., Lindquist, R. and Lindgren, G.: Optimal prediction of catastrophes in ARMA-processes., TFMS-3117.
  18. Frigyesi, A. and Hössjer, O.: On the behavior of kernel density estimators for singular and absolutely continuous distribution functions., NFMS-3161.
  19. Rychlik, I., Johannesson, P. and Leadbetter, M.R.: Modeling and statistical analysis of ocean-wave data using transformed Gaussian processes., NFMS-3160.
  20. Jones, M.C. and Hössjer, O.: From basic to reduced bias kernel density estimators: links via Taylor series approximations., NFMS-3159.
  21. Arvastson, L., Olsson, H. and Holst, J.: Parameter distribution in exponential forgetting., TFMS-3116.
  22. Sadegh, P., Holst, J., Madsen, H. and Melgaard, H.: Experiment design for grey-box identification., NFMS-3115.
  23. Arvastson, L. and Holst, J.: A physically based stochastic model for the power load on a district heating network., TFMS-3114.
  24. Perfekt, R.: Local extreme behaviour of dth order Markov chains., NFMS-3158.
  25. Rychlik, I.: A note on significant wave height., NFMS-3157.
  26. Gustafsson, R., Hössjer, O. and Öberg, T.: Adaptive detection of known signals in additive noise by means of kernel density estimators., NFMS-3156.
  27. Rosenqvist, A. Hössjer, O. and Holst, J.: Regression diagnostics using residuals and prediction matrix., TFMS-3113.
  28. Rosenqvist, A. Hössjer, O. and Holst, J.: Robust simple regression using the Hough transform., TFMS-3112.
  29.  Jacobsson, C., Jönsson, L., Lindgren, G. and Nyberg-Werther, M.: Werther identification of quark-gluon combinations by means of a synthetically trained neural net., TFMS-3111.
  30. Holmquist, B.: Simulation of multimodal circular distributions  of wrapped cauchy type of von Mises type., TFMS-3110.
  31. Holst, U., Hössjer, O., Björklund, C. et al: Locally weighted least squares kernel regression and statistical evaluation of LIDAR measurements., TFMS-3109.
  32. Gyllerup, S., Lanke, J., Lindgren, S-O. and Lindholm, L.: Changing drinking water hardness did not affect coronary mortality.
  33. Johannesson, P., Lindgren, G. and Rychlik, I.: Rainflow modelling of random vehicle fatigue loads., ITM report 1995:5, October 1995.


  1. Holmquist, B.: The d-variate vector hermite polynomial of order k., TFMS-3108.
  2. Holmquist, B.: Expectations of products of quadratic forms in normal variables., TFMS-3107.
  3. Egorov, V.: Limit theorems for order statistics and the operator of nondecreasing rearrangement., NFMS-3155.
  4. Rychlik, I.: Fatigue and stochastic loads., NFMS-3154.
  5. Grainger, R.W., Holst, J., Isaksson, A.J. and Ninness, B.M.: A parametric statistical approach to FDI for the Industrial Actuator Benchmark., TFMS-3106.
  6. Lindoff, B. and Holst, J.: Distribution of the RLS-estimator in a time-varying AR(1)-process., TFMS-3105.
  7. Hössjer, O.: Asymptotic bias and variance for a general class of varying bandwidth density estimators., TFMS-3104.
  8. Rychlik, I.: Extremes, rainflow cycles and damage functionals in continuous random processes., NFMS-3153.
  9. Anevski, D.: Estimating the derivative of a convex density., NFMS-3152.
  10. Hössjer, O.: Incomplete generalized L-statistics., TFMS-3103.
  11. Michna, Z.: Approximation of stochastic differential equations driven by alpha-Lévy motion., NFMS-3151.
  12. Pettersson, R.: Yosida approximations for multivalued stochastic differential equations., NFMS-3150.
  13. Piterbarg, V. and Rychlik, I.: Central limit theorem for wave-functionals of Gaussian processes., NFMS-3149.
  14. Piterbarg, V.: High level excursions of Gaussian fields and the optimal choice of the smoothing parameter., NFMS-3148.
  15. Lindgren, G. and Rychlik, I.: How reliable are contour curves - confidence sets for level contours., TFMS-3102.
  16. Hössjer, O. and Mielniczuk, J.: Delta method for long-range dependent observations., TFMS-3101.

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Last modified:  March 13, 2008.