Mixed Frequency Data Sampling Regression Models: The R Package midasr

When modeling economic relationships it is increasingly common to encounter data sampled at different frequencies. We introduce the R package midasr which enables estimating regression models with variables sampled at different frequencies within a MIDAS regression framework put forward in work by Ghysels, Santa-Clara, and Valkanov (2002). In this article we define a general autoregressive MIDAS regression model with multiple variables of different frequencies and show how it can be specified using the familiar R formula interface and estimated using various optimization methods chosen by the researcher. We discuss how to check the validity of the estimated model both in terms of numerical convergence and statistical adequacy of a chosen regression specification, how to perform model selection based on a information criterion, how to assess forecasting accuracy of the MIDAS regression model and how to obtain a forecast aggregation of different MIDAS regression models. We illustrate the capabilities of the package with a simulated MIDAS regression model and give two empirical examples of application of MIDAS regression

Seasonal renewal time variability in the Curonian Lagoon caused by atmospheric and hydrographical forcing

The aim of this study was to investigate the variability of the water exchanges in the Curonian Lagoon based on the hydraulic regime and the atmospheric forcings. A finite element hydrodynamic model has been applied to the Curonian Lagoon to simulate the circulation patterns for 10 years. With the help of a transport–diffusion model, the salinity distribution and the renewal times of the Curonian Lagoon have been investigated when forced by river runoff, wind, and Baltic Sea level fluctuations. The hydrodynamic model has been validated using in situ salinity measurements. Model results show that the variability depends mainly on seasonal changes in hydrographic forcing and on the dominant wind regimes that prevail over the Curonian Lagoon. Exchanges between the southern and the northern part of the lagoon mostly depend on the wind forcing and are much less influenced by the river discharge. However, when looking at the water renewal time, the most important factor is the river discharge into the lagoon. Other physical forcings only marginally determine the renewal time, and not even ice cover is able to influence it. Even if ice cover strongly inhibits the exchanges between the southern and northern lagoon, it is basically not able to change the absolute value of the renewal times

Cooking fish and drinking milk? Patterns in pottery use in the southeastern Baltic, 3300–2400 cal BC

yesA study of pottery vessel contents and use was undertaken in order to obtain information on food processed in Subneolithic and Neolithic vessels from Nida and Šventoji (3300–2400 cal BC). The aim is to assess pottery use during major changes in the coastal environment and in material culture. Bulk carbon and nitrogen isotope, lipid biomarker and compound specific carbon isotope analysis was undertaken on ‘foodcrusts’, charred deposits adhering to vessel surfaces, and absorbed residues from different vessel types. In addition, three archaeological seal bones were analysed for bulk collagen and compound specific carbon isotope analysis to establish collagen-lipid offsets to inform interpretation of the data. The results show that the majority of the vessels were used for processing aquatic products. At Nida the data suggest exploitation of freshwater resources and, in the later stages of occupation, dairying. Analysis of a small number of Subneolithic vessels from Šventoji produced results that are also consistent with processing of aquatic products. Other substances identified include Pinaceae sp. resin or tar and beeswax. These data demonstrate that identifying patterns in pottery use contributes to understanding Neolithisation processes

Drivers of Cyanobacterial Blooms in a Hypertrophic Lagoon

The Curonian Lagoon is Europe's largest lagoon and one of the most seriously impacted by harmful blooms of cyanobacteria. Intensive studies over the past 20 years have allowed us to identify the major drivers determining the composition and spatial extent of hyperblooms in this system. We summarize and discuss the main outcomes of these studies and provide an updated, conceptual scheme of the multiple interactions between climatic and hydrologic factors, and their influence on internal and external processes that promote cyanobacterial blooms. Retrospective analysis of remote sensed images demonstrated the variability of blooms in terms of timing, extension and intensity, suggesting that they occur only under specific circumstances. Monthly analysis of nutrient loads and stoichiometry from the principal tributary (Nemunas River) revealed large interannual differences in the delivery of key elements, but summer months were always characterized by a strong dissolved inorganic N (and Si) limitation, that depresses diatoms and favors the dominance of cyanobacteria. Cyanobacteria blooms occurred during high water temperatures, long water residence time and low-wind conditions. The blooms induce transient (night-time) hypoxia, which stimulates the release of iron-bound P, producing a positive feedback for blooms of N-fixing cyanobacteria. Consumer-mediated nutrient recycling by dreissenid mussels, chironomid larvae, cyprinids and large bird colonies, may also affect P availability, but their role as drivers of cyanobacteria blooms is understudied

Apie Donsker–Prokhorov invariantiškumo principo apibendrinimą

The extension of Donsker–Prokhorov invariance principle for two-dimensional parameter summation process in Hölder space is provided for the case of independent non-identically distributed random variables.Šiame straipsnyje yra apibendrinamas Donsker–Prokhorov invariantiškumo principas dvimačio indekso sumavimo procesui serijų schemoje. &nbsp

Principe d'invariance pour processus de sommation multiparamétrique et applications

A thèse a pour objet de prouver le principe d'invariance dans des espaces de Hölder pour le processus de sommation multiparamétrique et d'utiliser ce résultat en détection de rupture dans des données de panel. On caractérise d'abord la convergence en loi dans un espace de Hölder, du processus de sommation multiparamétrique dans le cas d'un champ aléatoire i.i.d. d'éléments aléatoires centrés et de carré intégrable d'un espace de Hilbert séparable, par la finitude d'un certain moment faible dont l'ordre croît avec l'exposant de Hölder, depuis deux lorsque l'exposant est nul, jusqu'à l'infini lorsque l'exposant est un demi. Ensuite on considère les tableaux triangulaires centrés à valeurs réelles. On propose une construction adaptative du processus de sommation qui coïncide avec la construction classique pour le cas d'un seul paramètre. On prouve le théorème limite central fonctionnel hölderien pour ce processus. Le processus limite est gaussien sous certaines conditions de régularité pour les variances du tableau triangulaire, le drap de Wiener n'étant qu'un cas particulier. Enfin on fournit des applications de ces résultats théoriques en construisant des statistiques de détection de rupture épidémique dans un ensemble de données multi-indexées. On construit un test de détection d'un changement d'espérance dans un rectangle épidémique, trouve sa loi limite et donne des conditions pour sa consistance. On adapte notre statistique pour la détection de rupture du coefficient dans les modèles classiques de régression pourpanel.The thesis is devoted to proving invariance principle in Hëlder spaces for the multi-parameter summation process and then using this resull to construct the tests for detecting' structural breaks in panel data. First we characterize the weak convergence in Hëlder space of multi-parameter summation process in the case of Li.d. random field of square integrable centered random elements in the separable Hilbert space by the finiteness of the certain weak moment, whose order increases with the Hblder exponent, turning to two, when exponent is zero and ta infinity when exponent is one hait. Next we consider real valued centered triangular arrays. We propose adaptive construction of the summation process which coincides with classical construction for the one parameter case. We prove the functional central Iimit theorem for this process in Hëlder space. The limiting process is Gaussian under certain regularity condition for variances of the triangular array, Wlener sheet being the special case. Finally we provide sorne application of the theoretical results by constructing statistics for detecting the epidemic change in a given data with multi-dimensional indexes. We construct a test for detecting the change of the mean in a epidemic rectangle, find its asymptotic distribution and give the conditions for the consistency. We adapt our proposed statistic for detecting the change of the coefficient in the classical panel regression models

Invariance principle for multiparameter summation processes and applications

LILLE1-BU (590092102) / SudocSudocFranceF