Modeling and forecasting electricity spot prices: A functional data perspective

Classical time series models have serious difficulties in modeling and forecasting the enormous fluctuations of electricity spot prices. Markov regime switch models belong to the most often used models in the electricity literature. These models try to capture the fluctuations of electricity spot prices by using different regimes, each with its own mean and covariance structure. Usually one regime is dedicated to moderate prices and another is dedicated to high prices. However, these models show poor performance and there is no theoretical justification for this kind of classification. The merit order model, the most important micro-economic pricing model for electricity spot prices, however, suggests a continuum of mean levels with a functional dependence on electricity demand. We propose a new statistical perspective on modeling and forecasting electricity spot prices that accounts for the merit order model. In a first step, the functional relation between electricity spot prices and electricity demand is modeled by daily price-demand functions. In a second step, we parameterize the series of daily price-demand functions using a functional factor model. The power of this new perspective is demonstrated by a forecast study that compares our functional factor model with two established classical time series models as well as two alternative functional data models.Comment: Published in at http://dx.doi.org/10.1214/13-AOAS652 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Skin Cell Proliferation Stimulated by Microneedles

A classical wound may be defined as a disruption of tissue integrity. Wounds, caused by trauma from accidents or surgery, that close via secondary intention rely on the biological phases of healing, i.e., hemostasis, inflammation, proliferation, and remodeling (HIPR). Depending on the wound type and severity, the inflammation phase begins immediately after injury and may last for an average of 7–14 days. Concurrent with the inflammation phase or slightly delayed, cell proliferation is stimulated followed by the activation of the remodeling (maturation) phase. The latter phase can last as long as 1 year or more, and the final healed state is represented by a scar tissue, a cross-linked collagen formation that usually aligns collagen fibers in a single direction. One may assume that skin microneedling that involves the use of dozens or as many as 200 needles that limit penetration to 1.5 mm over 1 cm2 of skin would cause trauma and bleeding followed by the classical HIPR. However, this is not the case or at least the HIPR phases are significantly curtailed and healing never ends in a scar formation. Conversely dermabrasion used in aesthetic medicine for improving skin quality is based on “ablation” (destruction or wounding of superficial skin layers), which requires several weeks for healing that involves formation of new skin layers. Such procedures provoke an acute inflammatory response. We believe that a less intense inflammatory response occurs following microneedle perforation of the skin. However, the mechanism of action of microneedling appears to be different. Here we review the potential mechanisms by which microneedling of the skin facilitates skin repair without scarring after the treatment of superficial burns, acne, hyperpigmentation, and the non-advancing periwound skin surrounding the chronic ulcerations of the integument

Estimation of the Semiparametric Factor Model: Application to Modelling Time Series of Electricity Spot Prices.

Classical univariate and multivariate time series models have problems to deal with the high variability of hourly electricity spot prices. We propose to model alternatively the daily mean electricity supply functions using a dynamic factor model. And to derive, subsequently, the hourly electricity spot prices by the evaluation of the estimated supply functions at the corresponding hourly values of demand for electricity. Supply functions are price (EUR/MWh) functions, that increase monotonically with demand for electricity (MW). Apart from this new conceptual approach, that allows us to represent the auction design of energy exchanges in a most natural way, our main contribution is an extraordinary simple algorithm to estimate the factor structure of the dynamic factor model. We decompose the time series into a functional spherical component and an univariate scaling component. The elements of the spherical component are all standardized having unit size such that we can robustly estimate the factor structure. This algorithm is much simpler than procedures suggested in the literature. In order to use a parsimonious labeling we will refer to the daily mean supply curves simply as price curves.Factor Analysis; functional time series data; sparse data; electricity spot market prices; European Electricity Exchange (EEX)

Effect of thiols on beta 2-adrenoceptors in human mononuclear leucocytes

The effect of the disulfide reducing agent dithiothreitol (DTT) and other thiols on binding of the beta-adrenoceptor antagonist (-)-125iodocyanopindolol (125ICYP) to human mononuclear leucocytes (MNL) was investigated. Saturation experiments and dissociation kinetics revealed two classes of specific 125ICYP binding sites, one of high and the other of low affinity, respectively. In intact MNL DTT caused a decrease in specific binding. This was due almost selectively to a decrease in the affinity of high affinity binding sites, which decreased gradually in a concentration-dependent manner to the affinity of low affinity binding sites. In MNL membranes DTT decreased not only the affinity but also the number of high affinity binding sites. The DTT effect was completely reversible by simple reoxidation on air. The structural isomers (+/-)-DTT. (-)-DTT and dithioerythritol revealed identical effects on specific binding, whereas the monothiols mercaptoethanol and alpha-monothioglycerol, having a lower redox potential, were considerably less effective. In the same concentration range that influenced specific binding. DTT stimulated intracellular cAMP production. These results suggest functionally important disulfide bridges which regulate the affinity of beta-adrenoceptor binding sites in human MNL. They stabilize the receptor in a high affinity state; their reduction causes the conversion of the high affinity state into a low affinity state in a process associated with stimulation of adenylate cyclase. Available evidence indicates that a similar transformation is made by beta-adrenoceptor agonists. Consequently low affinity 125ICYP binding sites preexistent in untreated cells could represent a reduced receptor state resulting from agonist-receptor interaction in vivo

The R-package phtt: Panel Data Analysis with Heterogeneous Time Trends

The R-package phtt provides estimation procedures for panel data with large dimensions n, T, and general forms of unobservable heterogeneous effects. Particularly, the estimation procedures are those of Bai (2009) and Kneip, Sickles, and Song (2012), which complement one another very well: both models assume the unobservable heterogeneous effects to have a factor structure. Kneip et al. (2012) considers the case in which the time varying common factors have relatively smooth patterns including strongly positive auto-correlated stationary as well as non-stationary factors, whereas the method of Bai (2009) focuses on stochastic bounded factors such as ARMA processes. Additionally, the phtt package provides a wide range of dimensionality criteria in order to estimate the number of the unobserved factors simultaneously with the remaining model parameters