• Communications for Statistical Applications and Methods
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• v.24 no.1
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• pp.1-13
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• 2017

This manuscript summarized advances in bootstrap methods for long-range dependent time series data. The stationary linear long-memory process is briefly described, which is a target process for bootstrap methodologies on time-domain and frequency-domain in this review. We illustrate time-domain bootstrap under long-range dependence, moving or non-overlapping block bootstraps, and the autoregressive-sieve bootstrap. In particular, block bootstrap methodologies need an adjustment factor for the distribution estimation of the sample mean in contrast to applications to weak dependent time processes. However, the autoregressive-sieve bootstrap does not need any other modification for application to long-memory. The frequency domain bootstrap for Whittle estimation is provided using parametric spectral density estimates because there is no current nonparametric spectral density estimation method using a kernel function for the linear long-range dependent time process.

• The Korean Journal of Applied Statistics
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• v.32 no.1
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• pp.69-81
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• 2019

We consider bivariate long range dependent (LRD) time series forecasting using a deep learning method. A long short-term memory (LSTM) network well-suited to time series data is applied to forecast bivariate time series; in addition, we compare the forecasting performance with bivariate fractional autoregressive integrated moving average (FARIMA) models. Out-of-sample forecasting errors are compared with various performance measures for functional MRI (fMRI) data and daily realized volatility data. The results show a subtle difference in the predicted values of the FIVARMA model and VARFIMA model. LSTM is computationally demanding due to hyper-parameter selection, but is more stable and the forecasting performance is competitively good to that of parametric long range dependent time series models.

• Journal of Welding and Joining
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• v.14 no.1
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• pp.38-46
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• 1996

High temperature low cycle fatigue crack growth behavior is investigated over a range of two temperatures and various frequencies in SUS 304 stainless steel. It is found that low frequency and temperature can enhance time-dependent crack growth. With high temperature, low frequency and long crack length, ${\Delta}J_c/{\Delta}J_ f$, the ratio of creep J integral range to fatigue J integral range is increased and time-dependent crack growth is accelerated. Interaction between ${\Delta}J_f$ and ${\Delta}J_c$ is occured at high frequency and low temparature and ${\Delta}J_c$, creep J integral range is fracture mechanical parameter on transition from cycle-dependent to time dependent crack growth in creep temperature region.

• Journal of the Korean Mathematical Society
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• v.40 no.1
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• pp.87-107
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• 2003

In this paper, we consider a discrete time queueing system fed by a superposition of an ON and OFF source with heavy tail ON periods and geometric OFF periods and a D-BMAP (Discrete Batch Markovian Arrival Process). We study the tail behavior of the queue length distribution and both infinite and finite buffer systems are considered. In the infinite buffer case, we show that the asymptotic tail behavior of the queue length of the system is equivalent to that of the same queueing system with the D-BMAP being replaced by a batch renewal process. In the finite buffer case (of buffer size K), we derive upper and lower bounds of the asymptotic behavior of the loss probability as $K\;\longrightarrow\;\infty$.

• Applied Microscopy
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• v.28 no.3
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• pp.415-424
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• 1998

The dependency of long-range order parameter on the ordered structure of $Pb(Mg_{1/3}Nb_{2/3})O_3$ solid solutions has been investigated by means of computer simulations of high-resolution lattice images. The computer image simulations were performed by the multislice method in a wide range of sample thicknesses, defocusing values, and long-range order parameters. It was found that the lattice images of the ordered structures were predominantly dependent on the long-range order parameter, The lattice images in a complete ordered structure showed a pseudo-hexagonal pattern. As the order parameter decreases, the simulated images changed slowly from a pseudo-hexagonal pattern to a rectangular pattern. The lattice images in a complete disordered structure showed a rectangular pattern. Also, the simulated images of the $Pb(Mg_xNb_{1-x})O_3$ with different Mg:Nb ratios obtained at a given long-range order parameter were basically the same patterns, irrespective of Mg and Nb compositions.

• Korean Journal of Applied Biomechanics
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• v.21 no.4
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• pp.397-403
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• 2011

The purpose of this study is to analyze the immediate effects of five toed shoes on foot structure. Subjects consisted of 26 college-aged women with pes planus. X-ray analysis of student feet were performed both barefooted and with five toed shoes. Dependent variables were hallux valgus angle, calcaneal inclination angle, 1st metatarsal declination angle, and intermetartarsal angle. Independent t-test was used for statistical analysis along with SAS. Overall, there were statistically significant changes of test subject's dependent variables when wearing five toed shoes. Specifically, the hallux valgus angle decreased, the calcaneal inclination angle and 1st metatarsal inclination angle increased, and intermetatasal angles both increased and decreased, shifting towards normal range. In every case the dependent variables shifted towards a more normal range while subjects wore five toed shoes. This study only examined the immediate corrective effects of five toed shoes on foot structure, but long-term studies are needed to understand the prolonged effects of five toed shoes on foot structure.

• Journal of Biosystems Engineering
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• v.39 no.4
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• pp.377-388
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• 2014

Purpose: Determining the spatial structure of data is important in understanding within-field variability for site-specific crop management. An understanding of the spatial structures present in the data may help illuminate interrelationships that are important in subsequent explanatory analyses, especially when site variables are correlated or are a combined response to multiple causative factors. Methods: In this study, correlation, principal component analysis, and single and nested variogram models were applied to soil electrical conductivity and chemical property data of two fields in central Missouri, USA. Results: Some variables that were highly correlated, or were strongly expressed in the same principal component, exhibited similar spatial ranges when fitted with a single variogram model. However, single variogram results were dependent on the active lag distance used, with short distances (30 m) required to fit short-range variability. Longer active lag distances only revealed long-range spatial components. Nested models generally yielded a better fit than single models for sensor-based conductivity data, where multiple scales of spatial structure were apparent. Gaussian-spherical nested models fit well to the data at both short (30 m) and long (300 m) active lag distances, generally capturing both short-range and long-range spatial components. As soil conductivity relates strongly to profile texture, we hypothesize that the short-range components may relate to the scale of erosion processes, while the long-range components are indicative of the scale of landscape morphology. Conclusion: In this study, we investigated the effect of changing active lag distance on the calculation of the range parameter. Future work investigating scale effects on other variogram parameters, including nugget and sill variances, may lead to better model selection and interpretation. Once this is achieved, separation of nested spatial components by factorial kriging may help to better define the correlations existing between spatial datasets.

• Journal of Communications and Networks
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• v.13 no.3
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• pp.286-297
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• 2011

A novel converged optical network unit (ONU)-base station (BS) architecture has been contemplated for next-generation optical-wireless networks. It has been demonstrated through high quality studies that data traffic carried by both wired and wireless networks exhibit self-similar and long range dependent characteristics; attributes that classical teletraffic theory based on simplistic Poisson models fail to capture. Therefore, in order to apprehend the proposed converged architecture and to reinforce the provisioning of tightly bound quality of service (QoS) parameters to end-users, we substantiate the analysis of the QoS behavior of the ONU-BS under self-similar and long range dependent traffic conditions using custom queuing which is a common queuing discipline. This paper extends our previous work on priority queuing and brings novelty in terms of presenting performance analysis of the converged ONU-BS under realistic traffic load conditions. Further, the presented analysis can be used as a network planning and optimization tool to select the most robust and appropriate queuing discipline for the ONU-BS relevant to the QoS requirements of different applications.

• The Korean Journal of Applied Statistics
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• v.26 no.6
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• pp.987-998
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• 2013

This paper considers the statistical characteristics on the air quality (PM10) of Korea collected hourly in 2011. PM10 in Korea exhibits very strong correlations even for higher lags, namely, long range dependence. It is power-law tailed in marginal distribution, and generalized Pareto distribution successfully captures the thicker tail than log-normal distribution. However, slowly decaying autocorrelations may confuse practitioners since a non-stationary model (such as changes in mean) can produce spurious long term correlations for finite samples. We conduct a statistical testing procedure to distinguish two models and argue that the high persistency can be explained by non-stationary changes in mean model rather than long range dependent time series models.

• The KIPS Transactions:PartC
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• v.11C no.5
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• pp.621-632
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• 2004

Recent measurement studies of real teletraffic data in modern telecommunication networks have shown that self-similar (or fractal) processes may provide better models of teletraffic in modern telecommunication networks than Poisson processes. If this is not taken into account, it can lead to inaccurate conclusions about performance of telecommunication networks. Thus, an important requirement for conducting simulation studies of telecommunication networks is the ability to generate long synthetic stochastic self-similar sequences. A new generator of pseu-do-random self-similar sequences, based on the fractional Gaussian nois and a wavelet transform, is proposed and analysed in this paper. Specifically, this generator uses Daubechies wavelets. The motivation behind this selection of wavelets is that Daubechies wavelets lead to more accurate results by better matching the self-similar structure of long range dependent processes, than other types of wavelets. The statistical accuracy and time required to produce sequences of a given (long) length are experimentally studied. This generator shows a high level of accuracy of the output data (in the sense of the Hurst parameter) and is fast. Its theoretical algorithmic complexity is 0(n).