Wyniki wyszukiwania

1

Artykuł dostępny w postaci pełnego tekstu - kliknij by otworzyć plik

Properties of efficient sequential plans for a birth and death process

100%

Różański R.

Mathematica Applicanda

|

1981

|

tom 9

|

nr 17

PL

W pracy udowodniono własności efektywnych planów sekwencyjnych dla procesu urodzin i śmierci o przeliczalnej ilości stanów. Podano przykłady takich planów.

EN

A birth and death process with parameters θ=(λ,μ), λ>0, μ>0, is considered. The absolute continuity of measures generated by this process is proved. The Rao-Cramér inequality for the variance of the unbiased estimator of a function h(θ) is derived. Some properties of the estimator attaining the Rao-Cramér lower bound are asserted.

2

On a strongly consistent estimator of the squared L_2-norm of a function

100%

Różański R.

Applicationes Mathematicae

|

1995-1996

|

tom 23

|

nr 3

279-284

EN

A kernel estimator of the squared $L_2$-norm of the intensity function of a Poisson random field is defined. It is proved that the estimator is asymptotically unbiased and strongly consistent. The problem of estimating the squared $L_2$-norm of a function disturbed by a Wiener random field is also considered.

3

G_{1,−1}-minimax estimation of the parameters of a distribution of exponential type

100%

Różański R.

Mathematica Applicanda

|

1978

|

tom 6

|

nr 13

PL

.

EN

The abstract is available at MR0518661.

4

On the consistency of sieve bootstrap prediction intervals for stationary time series

64%

Różański R., Zagdański A.

Discussiones Mathematicae Probability and Statistics

|

2004

|

tom 24

|

nr 1

5-40

EN

In the article, we consider construction of prediction intervals for stationary time series using Bühlmann's [8], [9] sieve bootstrapapproach. Basic theoretical properties concerning consistency are proved. We extend the results obtained earlier by Stine [21], Masarotto and Grigoletto [13] for an autoregressive time series of finite order to the rich class of linear and invertible stationary models. Finite sample performance of the constructed intervals is investigated by computer simulations.

5

Estimation of the hazard rate function with a reduction of bias and variance at the boundary

64%

Janiszewska B., Różański R.

Discussiones Mathematicae Probability and Statistics

|

2005

|

tom 25

|

nr 1

5-37

EN

In the article, we propose a new estimator of the hazard rate function in the framework of the multiplicative point process intensity model. The technique combines the reflection method and the method of transformation. The new method eliminates the boundary effect for suitably selected transformations reducing the bias at the boundary and keeping the asymptotics of the variance. The transformation depends on a pre-estimate of the logarithmic derivative of the hazard function at the boundary.

6

Estimation of the drift function for Ito processes and a class of semimartingales via histogram sieve

64%

Różański R., Zagdański A.

Applicationes Mathematicae

|

2006

|

tom 33

|

nr 1

21-40

EN

A histogram sieve estimator of the drift function in Ito processes and some semimartingales is constructed. It is proved that the estimator is pointwise and L¹ consistent and its finite-dimensional distributions are asymptotically normal. Our approach extends the results of Leśkow and Różański (1989a).

Ograniczanie wyników

2 Applicationes Mathematicae

2 Discussiones Mathematicae Probability and Statistics

2 Mathematica Applicanda

6 Różański R.

2 Zagdański A.

1 Janiszewska B.

1 2006

1 2005

1 2004

1 1995

1 1981

1 1978

Properties of efficient sequential plans for a birth and death process

On a strongly consistent estimator of the squared L_2-norm of a function

G_{1,−1}-minimax estimation of the parameters of a distribution of exponential type

On the consistency of sieve bootstrap prediction intervals for stationary time series

Estimation of the hazard rate function with a reduction of bias and variance at the boundary

Estimation of the drift function for Ito processes and a class of semimartingales via histogram sieve