Law of the Iterated Logarithm for U-Statistics of Weakly Dependent Observations

The law of the iterated logarithm for partial sums of weakly dependent processes was intensively studied by Walter Philipp in the late 1960s and 1970s. In this paper, we aim to extend these results to nondegenerate U-statistics of data that are strongly mixing or functionals of an absolutely regular process.Comment: typos corrrecte

Two-Sample U-Statistic Processes for Long-Range Dependent Data

Motivated by some common-change point tests, we investigate the asymptotic distribution of the U-statistic process $U_n(t)=\sum_{i=1}^{[nt]}\sum_{j=[nt]+1}^n h(X_i,X_j)$, $0\leq t\leq 1$, when the underlying data are long-range dependent. We present two approaches, one based on an expansion of the kernel $h(x,y)$ into Hermite polynomials, the other based on an empirical process representation of the U-statistic. Together, the two approaches cover a wide range of kernels, including all kernels commonly used in applications

Near Real-Time Disturbance Detection in Terrestrial Ecosystems Using Satellite Image Time Series: Drought Detection in Somalia

Near real-time monitoring of ecosystem disturbances is critical for addressing impacts on carbon dynamics, biodiversity, and socio-ecological processes. Satellite remote sensing enables cost-effective and accurate monitoring at frequent time steps over large areas. Yet, generic methods to detect disturbances within newly captured satellite images are lacking. We propose a generic time series based disturbance detection approach by modelling stable historical behaviour to enable detection of abnormal changes within newly acquired data. Time series of vegetation greenness provide a measure for terrestrial vegetation productivity over the last decades covering the whole world and contain essential information related land cover dynamics and disturbances. Here, we assess and demonstrate the method by (1) simulating time series of vegetation greenness data from satellite data with different amount of noise, seasonality and disturbances representing a wide range of terrestrial ecosystems, (2) applying it to real satellite greenness image time series between February 2000 and July 2011 covering Somalia to detect drought related vegetation disturbances. First, simulation results illustrate that disturbances are successfully detected in near real-time while being robust for seasonality and noise. Second, major drought related disturbance corresponding with most drought stressed regions in Somalia are detected from mid 2010 onwards and confirm proof-of-concept of the method. The method can be integrated within current operational early warning systems and has the potential to detect a wide variety of disturbances (e.g. deforestation, flood damage, etc.). It can analyse in-situ or satellite data time series of biophysical indicators from local to global scale since it is fast, does not depend on thresholds or definitions and does not require time series gap filling.early warning, real-time monitoring, global change, disturbance, time series, remote sensing, vegetation and climate dynamics

Has Carbon Disclosure Become More Transparent in the Global Logistics Industry? An Investigation of Corporate Carbon Disclosure Strategies between 2010 and 2015

Global logistics companies are increasingly disclosing carbon related information due to institutional and stakeholder pressures. Existing research, however, is limited to categorizing these pressures and their influences on corporate carbon disclosure strategies. In particular, literature to date has not distinguished between different carbon disclosure strategies and how they may have changed over time. In response, this paper: (1) proposes a framework that depicts four different carbon disclosure responses and strategies based on internal and external pressures; and (2) subsequently analyzes and compares corporate carbon disclosure strategies between 2010 and 2015. Using a sample of 39 leading global logistics companies, carbon disclosure strategies are categorized based on the analysis of 25 applied carbon management practices from Bloomberg ESG to see if carbon management practices and the associated strategies have changed. The findings show overall shifts to more transparent corporate carbon disclosure strategies between 2010 and 2015 with an increase of applied carbon management practices in both internal and external actions

A Systematic Review of Blockchain Literature in Logistics and Supply Chain Management: Identifying Research Questions and Future Directions

Potential blockchain applications in logistics and supply chain (LSCM) have gained increasing attention within both academia and industry. However, as a field in its infancy, blockchain research often lacks theoretical foundations, and it is not clear which and to what extent organizational theories are used to investigate blockchain technology in the field of LSCM. In response, based upon a systematic literature review, this paper: (a) identifies the most relevant organizational theories used in blockchain literature in the context of LSCM; and (b) examines the content of the identified organizational theories to formulate relevant research questions for investigating blockchain technology in LSCM. Our results show that blockchain literature in LSCM is based around six organizational theories, namely: agency theory, information theory, institutional theory, network theory, the resource-based view and transaction cost analysis. We also present how these theories can be used to examine specific blockchain problems by identifying blockchain-specific research questions that are worthy of investigation

A robust method for shift detection in time series

We present a robust test for change-points in time series which is based on the two-sample Hodges-Lehmann estimator. We develop new limit theory for a class of statistics based on the two-sample U-quantile processes, in the case of short range dependent observations. Using this theory we can derive the asymptotic distribution of our test statistic under the null hypothesis. We study the finite sample properties of our test via a simulation study and compare the test with the classical CUSUM test and a test based on the Wilcoxon- Mann-Whitney statistic

Near Real-Time Disturbance Detection in Terrestrial Ecosystems Using Satellite Image Time Series: Drought Detection in Somalia

The article promotes an innovative method of monitoring of ecosystems that uses satellite data to detect drought.Maqaalku wuxuu tala ahaan soo jeedinayaa hab cusub oo lagu kormeero hab-wadanoolaashaha, iyagoo la adeegsanayo xitaa sawirro dayaxgacmeed si loo sahmiyo abaaraha.L'articolo propone un metodo innovativo di monitoraggio degli ecosistemi che utilizza anche immagini satellitari per il rilevamento delle siccità