Informacja

Drogi użytkowniku, aplikacja do prawidłowego działania wymaga obsługi JavaScript. Proszę włącz obsługę JavaScript w Twojej przeglądarce.

English (EN)·Polski (PL)·Yкраїнський (UK)
Przejdź do strony domowej biblioteki Centralna Biblioteka Wojskowa Link otwiera się w nowym oknie Logo biblioteki Prolib Integro - strona głównaCentralna Biblioteka Wojskowa

Wyszukujesz frazę "least squares estimator" wg kryterium: Temat

  Lista filtrów
Wyrównaj
    Wyświetlanie 1-10 z 10
    Tytuł:
    An alternative approach to characterize the commutativity of orthogonal projectors
    Autorzy:
    Baksalary, Oskar
    Trenkler, Götz
    Powiązania:
    https://bibliotekanauki.pl/articles/729960.pdf
    Data publikacji:
    2008
    Wydawca:
    Uniwersytet Zielonogórski. Wydział Matematyki, Informatyki i Ekonometrii
    Tematy:
    partitioned matrix
    canonical correlations
    ordinary least squares estimator
    generalized least squares estimator
    best linear unbiased estimator
    Opis:
    In an invited paper, Baksalary [Algebraic characterizations and statistical implications of the commutativity of orthogonal projectors. In: T. Pukkila, S. Puntanen (Eds.), Proceedings of the Second International Tampere Conference in Statistics, University of Tampere, Tampere, Finland, [2], pp. 113-142] presented 45 necessary and sufficient conditions for the commutativity of a pair of orthogonal projectors. Basing on these results, he discussed therein also statistical aspects of the commutativity with reference to problems concerned with canonical correlations and with comparisons between estimators and between sets of linearly sufficient statistics corresponding to different linear models. In the present paper, parts of this analysis are resumed in order to shed some additional light on the problem of commutativity. The approach utilized is different than the one used by Baksalary, and is based on representations of projectors in terms of partitioned matrices. The usefulness of such representations is demonstrated by reinvestigating some of Baksalary's statistical considerations.
    Źródło:
    Discussiones Mathematicae Probability and Statistics; 2008, 28, 1; 113-137
    1509-9423
    Pojawia się w:
    Discussiones Mathematicae Probability and Statistics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Estimation of the density and cumulative distribution functions of the exponentiated Burr XII distribution
    Autorzy:
    Hassan, Amal S.
    Assar, Salwa M.
    Ali, Kareem A.
    Nagy, Heba F.
    Powiązania:
    https://bibliotekanauki.pl/articles/1917020.pdf
    Data publikacji:
    2021-12-08
    Wydawca:
    Główny Urząd Statystyczny
    Tematy:
    exponentiated Burr Type XII model
    least squares estimator
    maximum likelihood estimator
    uniform minimum variance unbiased estimator
    weighted least squares estimator
    Opis:
    The exponentiated Burr Type XII (EBXII) distribution has wide applications in reliability and economic studies. In this article, the estimation of the probability density function and the cumulative distribution function of EBXII distribution is considered. We examine the maximum likelihood estimator, the uniformly minimum variance unbiased estimator, the least squares estimator, the weighted least squares estimator, the maximum product spacing estimator, the Cramér–von-Mises estimator, and the Anderson–Darling estimator. We derive analytical forms for the bias and mean square error. A simulation study is performed to investigate the consistency of the suggested methods of estimation. Data relating to the wind speed and service times of aircraft windshields are used with the studied methods. The simulation studies and real data applications have revealed that the maximum likelihood estimator performs more efficiently than its remaining counterparts.
    Źródło:
    Statistics in Transition new series; 2021, 22, 4; 171-189
    1234-7655
    Pojawia się w:
    Statistics in Transition new series
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Sufficient conditions for the strong consistency of least squares estimator with α-stable errors
    Autorzy:
    Mexia, João
    da Silva, João
    Powiązania:
    https://bibliotekanauki.pl/articles/729990.pdf
    Data publikacji:
    2007
    Wydawca:
    Uniwersytet Zielonogórski. Wydział Matematyki, Informatyki i Ekonometrii
    Tematy:
    linear models
    least squares estimator
    strong consistency
    stability
    Opis:
    Let $Y_{i} = x_{i}^{T}β + e_{i}$, 1 ≤ i ≤ n, n ≥ 1 be a linear regression model and suppose that the random errors e₁, e₂, ... are independent and α-stable. In this paper, we obtain sufficient conditions for the strong consistency of the least squares estimator β̃ of β under additional assumptions on the non-random sequence x₁, x₂,... of real vectors.
    Źródło:
    Discussiones Mathematicae Probability and Statistics; 2007, 27, 1-2; 27-45
    1509-9423
    Pojawia się w:
    Discussiones Mathematicae Probability and Statistics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Least squares estimator consistency: a geometric approach
    Autorzy:
    Mexia, João
    da Silva, João
    Powiązania:
    https://bibliotekanauki.pl/articles/729688.pdf
    Data publikacji:
    2006
    Wydawca:
    Uniwersytet Zielonogórski. Wydział Matematyki, Informatyki i Ekonometrii
    Tematy:
    linear models
    least squares estimator
    consistency
    radial symmetry
    generalized polar coordinates
    Opis:
    Consistency of LSE estimator in linear models is studied assuming that the error vector has radial symmetry. Generalized polar coordinates and algebraic assumptions on the design matrix are considered in the results that are established.
    Źródło:
    Discussiones Mathematicae Probability and Statistics; 2006, 26, 1; 19-45
    1509-9423
    Pojawia się w:
    Discussiones Mathematicae Probability and Statistics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    On-line parameter and delay estimation of continuous-time dynamic systems
    Autorzy:
    Kozłowski, J.
    Kowalczuk, Z.
    Powiązania:
    https://bibliotekanauki.pl/articles/330669.pdf
    Data publikacji:
    2015
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    delay system
    continuous time model
    discrete approximation
    parameter estimation
    least squares estimator
    instrumental variable estimator
    układ z opóźnieniem
    aproksymacja dyskretna
    estymacja parametrów
    zmienna instrumentalna
    Opis:
    The problem of on-line identification of non-stationary delay systems is considered. The dynamics of supervised industrial processes are usually modeled by ordinary differential equations. Discrete-time mechanizations of continuous-time process models are implemented with the use of dedicated finite-horizon integrating filters. Least-squares and instrumental variable procedures mechanized in recursive forms are applied for simultaneous identification of input delay and spectral parameters of the system models. The performance of the proposed estimation algorithms is verified in an illustrative numerical simulation study.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2015, 25, 2; 223-232
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    An efficient algorithm for estimating the parameters of superimposed exponential signals in multiplicative and additive noise
    Autorzy:
    Bian, J.
    Peng, H.
    Xing, J.
    Liu, Z.
    Li, H.
    Powiązania:
    https://bibliotekanauki.pl/articles/331007.pdf
    Data publikacji:
    2013
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    superimposed exponential signals
    modified Newton–Raphson algorithm
    multiplicative noise
    additive noise
    least squares estimator
    algorytm Newtona-Raphsona
    metoda najmniejszych kwadratów
    estymator
    Opis:
    This paper considers parameter estimation of superimposed exponential signals in multiplicative and additive noise which are all independent and identically distributed. A modified Newton–Raphson algorithm is used to estimate the frequencies of the considered model, which is further used to estimate other linear parameters. It is proved that the modified Newton–Raphson algorithm is robust and the corresponding estimators of frequencies attain the same convergence rate with Least Squares Estimators (LSEs) under the same noise conditions, but it outperforms LSEs in terms of the mean squared errors. Finally, the effectiveness of the algorithm is verified by some numerical experiments.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2013, 23, 1; 117-129
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Intelligent financial time series forecasting: A complex neuro-fuzzy approach with multi-swarm intelligence
    Autorzy:
    Li, C.
    Chiang, T. W.
    Powiązania:
    https://bibliotekanauki.pl/articles/331280.pdf
    Data publikacji:
    2012
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    zbiór rozmyty
    system neuronowo-rozmyty
    optymalizacja rojem cząstek
    szereg czasowy
    complex fuzzy set
    complex neuro fuzzy system
    hierarchical multi swarm
    particle swarm optimization (PSO)
    recursive least squares estimator
    time series forecasting
    Opis:
    Financial investors often face an urgent need to predict the future. Accurate forecasting may allow investors to be aware of changes in financial markets in the future, so that they can reduce the risk of investment. In this paper, we present an intelligent computing paradigm, called the Complex Neuro-Fuzzy System (CNFS), applied to the problem of financial time series forecasting. The CNFS is an adaptive system, which is designed using Complex Fuzzy Sets (CFSs) whose membership functions are complex-valued and characterized within the unit disc of the complex plane. The application of CFSs to the CNFS can augment the adaptive capability of nonlinear functional mapping, which is valuable for nonlinear forecasting. Moreover, to optimize the CNFS for accurate forecasting, we devised a new hybrid learning method, called the HMSPSO-RLSE, which integrates in a hybrid way the so-called Hierarchical Multi-Swarm PSO (HMSPSO) and the well known Recursive Least Squares Estimator (RLSE). Three examples of financial time series are used to test the proposed approach, whose experimental results outperform those of other methods.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2012, 22, 4; 787-800
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Consistency of trigonometric and polynomial regression estimators
    Autorzy:
    Popiński, Waldemar
    Powiązania:
    https://bibliotekanauki.pl/articles/1339065.pdf
    Data publikacji:
    1998
    Wydawca:
    Polska Akademia Nauk. Instytut Matematyczny PAN
    Tematy:
    consistent estimator
    orthonormal system
    least squares method
    regression
    Opis:
    The problem of nonparametric regression function estimation is considered using the complete orthonormal system of trigonometric functions or Legendre polynomials $e_k$, k=0,1,..., for the observation model $y_i = f(x_i) + η_i $, i=1,...,n, where the $η_i$ are independent random variables with zero mean value and finite variance, and the observation points $x_i\in[a,b]$, i=1,...,n, form a random sample from a distribution with density $ϱ\in L^1[a,b]$. Sufficient and necessary conditions are obtained for consistency in the sense of the errors $\Vert f-\widehat f_N\Vert, \vert f(x)-\widehatf_N(x)\vert$, $x\in[a,b]$, and $E\Vert f-\widehatf_N\Vert^2$ of the projection estimator $\widehat f_N(x) = \sum_{k=0}^N\widehat{c}_ke_k(x)$ for $\widehat{c}_0,\widehat{c}_1,\ldots,\widehat{c}_N$ determined by the least squares method and $f\in L^2[a,b]$.
    Źródło:
    Applicationes Mathematicae; 1998-1999, 25, 1; 73-83
    1233-7234
    Pojawia się w:
    Applicationes Mathematicae
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    On least squares estimation of Fourier coefficients and of the regression function
    Autorzy:
    Popiński, Waldemar
    Powiązania:
    https://bibliotekanauki.pl/articles/1340683.pdf
    Data publikacji:
    1993
    Wydawca:
    Polska Akademia Nauk. Instytut Matematyczny PAN
    Tematy:
    Fourier series
    consistent estimator
    least squares method
    regression
    Opis:
    The problem of nonparametric function fitting with the observation model $y_i = f(x_i) + η_i$, i=1,...,n, is considered, where $η_i$ are independent random variables with zero mean value and finite variance, and $x_i \in [a,b] \subset \R^1$, i=1,...,n, form a random sample from a distribution with density $ϱ \in L^1[a,b]$ and are independent of the errors $η_i$, i=1,...,n. The asymptotic properties of the estimator $\widehat{f}_{N(n)}(x) = \sum_{k=1}^{N(n)} \widehat{c}_ke_k(x)$ for $f \in L^2[a,b]$ and $\widehat{c}^{N(n)}=( \widehat{c}_1,..., \widehat{c}_{N(n)})^T$ obtained by the least squares method as well as the limits in probability of the estimators $\widehat{c}_k$, k=1,...,N, for fixed N, are studied in the case when the functions $e_k$, k=1,2,..., forming a complete orthonormal system in $L^2\[a,b\]$ are analytic.
    Źródło:
    Applicationes Mathematicae; 1993-1995, 22, 1; 91-102
    1233-7234
    Pojawia się w:
    Applicationes Mathematicae
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Least-squares trigonometric regression estimation
    Autorzy:
    Popiński, Waldemar
    Powiązania:
    https://bibliotekanauki.pl/articles/1338814.pdf
    Data publikacji:
    1999
    Wydawca:
    Polska Akademia Nauk. Instytut Matematyczny PAN
    Tematy:
    consistent estimator
    least squares method
    Fourier coefficients
    trigonometric polynomial
    regression function
    Opis:
    The problem of nonparametric function fitting using the complete orthogonal system of trigonometric functions $e_k$, k=0,1,2,..., for the observation model $y_i = f(x_{in}) + η_i$, i=1,...,n, is considered, where $η_i$ are uncorrelated random variables with zero mean value and finite variance, and the observation points $x_{in} ∈ [0,2π]$, i=1,...,n, are equidistant. Conditions for convergence of the mean-square prediction error $(1/n)\sum_{i=1}^n E(f(x_{in})-\widehat f_{N(n)}(x_{in}))^2$, the integrated mean-square error $E ‖f-\widehat f_{N(n)}‖^2$ and the pointwise mean-square error $E(f(x)-\widehatf_{N(n)}(x))^2$ of the estimator $\widehat f_{N(n)}(x) = \sum_{k=0}^{N(n)} \widehat c_k e_k(x)$ for f ∈ C[0,2π] and $\widehat c_0,\widehat c_1,...,\widehat c_{N(n)}$ obtained by the least squares method are studied.
    Źródło:
    Applicationes Mathematicae; 1999, 26, 2; 121-131
    1233-7234
    Pojawia się w:
    Applicationes Mathematicae
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-10 z 10

      Ta witryna wykorzystuje pliki cookies do przechowywania informacji na Twoim komputerze. Pliki cookies stosujemy w celu świadczenia usług na najwyższym poziomie, w tym w sposób dostosowany do indywidualnych potrzeb. Korzystanie z witryny bez zmiany ustawień dotyczących cookies oznacza, że będą one zamieszczane w Twoim komputerze. W każdym momencie możesz dokonać zmiany ustawień dotyczących cookies