A5070974341- Stochastic processes and statistical mechanics
- Financial Risk and Volatility Modeling
- Stochastic processes and financial applications
- Random Matrices and Applications
- Theoretical and Computational Physics
- Statistical Methods and Inference
- Monetary Policy and Economic Impact
- Machine Learning in Bioinformatics
- Fault Detection and Control Systems
- Bayesian Methods and Mixture Models
- Control Systems and Identification
- Complex Systems and Time Series Analysis
- Air Quality Monitoring and Forecasting
- Advanced Statistical Process Monitoring
- Mathematical Dynamics and Fractals
- Fuzzy Systems and Optimization
- Advanced Statistical Methods and Models
- Human Mobility and Location-Based Analysis
- Markov Chains and Monte Carlo Methods
- Data Management and Algorithms
- Traffic Prediction and Management Techniques
- Global trade and economics
- Vehicle emissions and performance
- Evacuation and Crowd Dynamics
- Vehicular Ad Hoc Networks (VANETs)
University of Debrecen
2014-2024
Alfréd Rényi Institute of Mathematics
2017
University of Szeged
2014
Hungarian Academy of Sciences
2002
Summary Environmental epidemiological studies of the health effects air pollution frequently utilize generalized additive model (GAM) as standard statistical methodology, considering ambient pollutants explanatory covariates. Although exposure to is multi-dimensional, majority these consider only a single pollutant covariate in GAM model. This restriction may be because variables do not have serial dependence but also interdependence between themselves. In an attempt convey more realistic...
Smart cities offer services to their inhabitants which make everyday life easier beyond providing a feedback channel the city administration. For instance, live timetable service for public transportation or real-time traffic jam notification can increase efficiency of travel planning substantially. Traditionally, implementation these smart require deployment some costly sensing and tracking infrastructure. As an alternative, crowd be involved in data collection via mobile devices. This...
This paper introduces a non-negative integer-valued autoregressive (INAR) process with seasonal structure of first order, which is an extension the standard INAR(1) model proposed by Al-Osh and Alzaid [First-order (INAR(1)) process. J Time Ser Anal. 1987;8:261–275]. The main properties are derived such as its stationarity autocorrelation function (ACF), among others. conditional least squares maximum likelihood estimators parameters studied their asymptotic established. Some detailed...
Modeling and simulating movement of vehicles in established transportation infrastructures, especially large urban road networks is an important task. It helps understanding handling traffic problems, optimizing regulations adapting the management real time for unexpected disaster events. A mathematically rigorous stochastic model that can be used analysis was proposed earlier by other researchers which based on interplay between graph Markov chain theories. This provides a transition...
We investigate a sequence of Galton-Watson branching processes with immigration, where the offspring mean tends to its critical value 1 and variance 0. It is shown that fluctuation limit an Ornstein-Uhlenbeck-type process. As consequence, in contrast case which positive limit, it transpires conditional least-squares estimator asymptotically normal. The norming factor n 3/2 , both subcritical case, 1/2 nearly limiting variance, .
A sequence of first-order integer-valued autoregressive (INAR(1)) processes is investigated, where the autoregressive-type coefficient converges to 1. It shown that limiting distribution conditional least squares estimator for this normal and rate convergence n 3/2 . Nearly critical Galton–Watson with unobservable immigration are also discussed.
ABSTRACT In this paper, the asymptotic behavior of conditional least squares estimators autoregressive parameters, mean innovations, and stability parameter for unstable integer‐valued processes order 2 is described. The limit distributions scaling factors are different according to following three cases: (i) decomposable, (ii) indecomposable but not positively regular, (iii) regular models.
Under natural assumptions a Feller-type diffusion approximation is derived for critical multi-type branching processes with immigration when the offspring mean matrix primitive (in other words, positively regular). Namely, it proved that sequence of appropriately scaled random step functions formed from converges weakly toward squared Bessel process supported by ray determined Perron vector matrix.
A modified version of the popular Lee-Carter method (Lee-Carter 1992) is applied to forecast mortality rates in Hungary for period 2004–2040 on basis data between 1949 and 2003 both men women. Another case also considered based a restricted set corresponding 1989–2003. The model fitted 1949–2003 forecasts increasing ages 45 55, pointing out that hardly applicable countries where exhibit trends as peculiar Hungary. However, models last 15 years women decreasing similarly was successfully...
Abstract We consider integer-valued autoregressive models of order one contaminated with innovational outliers. Assuming that the time points outliers are known but their sizes unknown, we prove Conditional Least Squares (CLS) estimators offspring and innovation means strongly consistent. In contrast, CLS outliers' not also joint estimator is asymptotically normal. Conditionally on values process at preceding occurrences, Keywords: asymptotic normalityConditional least squares...
In this paper, the asymptotic behavior of conditional least squares (CLS) estimators offspring means $(\alpha,\beta)$ and criticality parameter $\varrho:=\alpha+\beta$ for a 2-type critical doubly symmetric positively regular Galton–Watson branching process with immigration is described.
We investigate a sequence of Galton-Watson branching processes with immigration, where the offspring mean tends to its critical value 1 and variance 0. It is shown that fluctuation limit an Ornstein-Uhlenbeck-type process. As consequence, in contrast case which positive limit, it transpires conditional least-squares estimator asymptotically normal. The norming factor n 3/2 , both subcritical case, 1/2 nearly limiting variance, .
A spectral criterion involving the model parameters is given for existence and uniqueness of a periodically correlated seasonal non‐negative integer‐valued autoregressive process. The structure mean covariance functions stationary distribution derived using its implicit state‐space representation. Two infinite series representations process, moving average, immigrant generation, are established. Based on latter representation, novel parallelizable simulation method proposed to generate
An inhomogeneous first--order integer--valued autoregressive (INAR(1)) process is investigated, where the type coefficient slowly converges to one. It shown that weakly a Poisson or compound distribution.
Robocar World Championship or briefly OOCWC is a new initiative to create community of people who share their interest in investigating the relationship between smart cities and robot cars with particular attention spread near future. At heart this City Emulator. It intended offer common research platform for investigation city simulations. In paper, we review recent advances OOCWC.
Functional limit theorems are proved for a sequence of Galton-Watson processes with immigration, where the offspring mean tends to its critical value 1 under weak conditions variances and immigration processes.In norming factors depend on these variances.