Analysis of many short time sequences: Forecast improvements achieved by shrinkage

Credibility models in actuarial science deal with multiple short time series where each series represents claim amounts of different insurance groups. Commonly used credibility models imply shrinkage of group-specific estimates towards their average. In this paper we model the claim size yu in group i and at time t as the sum of three independent components: y_it = μ_r + δ_i + ?_it. The first component, μt = μ_t?1 + m_t, represents time-varying levels that are common to all groups. The second component, δ_i, represents random group offsets that are the same in all periods, and the third component represents independent measurement errors. In this paper we show how to obtain forecasts from this model and we discuss the nature of the forecasts, with particular emphasis on shrinkage. We also assess the forecast improvements that can be expected from such a model. Finally, we discuss an extension of the above model which also allows the group offsets to change over time. We assume that the offsets for different groups follow independent random walks.     

Combining experts' opinions using a normal-wishart model

This paper examines how a Bayesian decision maker might update her distributions for continuous variables X_i, i=1, 2, …, upon hearing experts' forecasts expressed as quantiles. To utilize the relationship between the decision maker and experts, and to avoid problems associated with different scales and ranges of the variables, we assume that the decision maker transforms the experts' quantiles in terms of her own prior distribution for each X_i. A model using such a transformation is presented and its properties are examined.     

Estimating and Predicting the General Random Effects Model

This paper extends the ‘remarkable property’ of Breusch (Journal of Econometrics 1987; 36 : 383–389) and Baltagi and Li (Journal of Econometrics 1992; 53 : 45–51) to the three‐way random components framework. Indeed, like its one‐way and two‐way counterparts, the three‐way random effects model maximum likelihood estimation can be obtained as an iterated generalized least squares procedure through an appropriate algorithm of monotonic sequences of some variance components ratios, θ_i (i = 2, 3, 4). More specifically, a search over θ_iwhile iterating on the regression coefficients estimates β and the other θ_jwill guard against the possibility of multiple local maxima of the likelihood function. In addition, the derivations of related prediction functions are obtained based on complete as well as incomplete panels. Finally, an application to international trade issues modeling is presented. Copyright © 2014 John Wiley & Sons, Ltd.     

Temporal Aggregation in Dynamic Linear Models

One important aspect concerning the analysis and forecasting of time series that is sometimes neglected is the relationship between a model and the sampling interval, in particular, when the observation is cumulative over the sampling period. This paper intends to study the temporal aggregation in Bayesian dynamic linear models (DLM). Suppose that a time series Y_t is observed at time units t and the observations of the process are aggregated over r units of time, defining a new time series Z_k=Σ^r_i=1Y_rk+i. The relevant factors explaining the variation of Z_k can, and in general will, be different, depending on how the sampling interval r is chosen. It is shown that if Y_t follows certain dynamic linear models, then the aggregated series can also be described by possibly different DLM. In the examples, the industrial production of Brazil is analysed under various aggregation periods and the results are compared. © 1997 John Wiley & Sons, Ltd.     

Forecasting for the generation of trading signals in financial markets

In this paper we show that optimal trading results can be achieved if we can forecast a key summary statistic of future prices. Consider the following optimization problem. Let the return r_i (over time i=1, 2, ..., n) for the ith day be given and the investor has to make investment decision d_i on the ith day with d_i=1 representing a ‘long' position and d_i=0 a ‘neutral' position. The investment return is given by r=Σⁿ_i=1r_id_i−cΣⁿ⁺¹_i=1∣d_i−d_i−1∣, where c is the transaction cost. The mathematical programming problem of choosing d₁, ..., d_n to maximize r under a given transaction cost c is shown to have an analytic solution, which is a function of a key summary statistic called the largest change before reversal. The largest change before reversal is recommended to be used as an output in a neural network for the generation of trading signals. When neural network forecasting is applied to a dataset of Hang Seng Index Futures Contract traded in Hong Kong, it is shown that forecasting the largest change before reversal outperforms the k‐step‐ahead forecast in achieving higher trading profits. Copyright © 2000 John Wiley & Sons, Ltd.     

Étude quantitative de la régénération caudale,avec ou sans moelle épinière,chez la larve de Salamandre

Summary Tail regeneration in the absence of spinal cord was studied quantitatively in larval salamanders. Growth parameters were calculated according to the function =1/ny _i /x _i (Rao).The regeneration rate of despinalized tails was found to be approximatively half the normal rate in both the length and volume.The real nature of despinalized tail regenerates is discussed and two hypotheses are proposed for their explanation.

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Travail exécuté grâce une subvention de la «DonationGeorges etAntoine Claraz, instituta et curataJohannis Schinz professoris auspiciis».     

Activation of CD47 receptors causes histamine secretion from mast cells

Mast cells play pivotal roles in allergic and inflammatory processes via distinct activation pathways. Mucosal and serosal mast cells are activated by the IgE/FcɛRI pathway, while only serosal mast cells are activated by basic secretagogues. We show that CD47 receptors are expressed on rat peritoneal mast cells. 4N1K, a peptide agonist of CD47, rapidly caused exocytosis. Such exocytosis required increased intracellular calcium and was inhibited by pertussis toxin and an antibody against the βγ dimer of a G_i protein. Cooperation with integrins and glycosylphosphatidylinositol-anchored proteins was necessary, since anti-integrin antibodies and pretreatment with phosphatidylinositol-phospholipase C reduced exocytosis. Depletion of membrane cholesterol inhibited exocytosis and decreased CD47 in lipid rafts, consistent with a CD47/integrin/G_i protein complex being located in rafts. An anti-CD47 antibody inhibited exocytosis induced by 4N1K and by mastoparan and spermine, suggesting that basic secretagogues might target CD47. We propose that 4N1K-stimulated mast cell exocytosis involves a CD47/integrin/G_i protein complex. Received 8 December 2008; received after revision 12 January 2009; accepted 29 January 2009     

A non‐Gaussian generalization of the Airline model for robust seasonal adjustment

In their seminal book Time Series Analysis: Forecasting and Control, Box and Jenkins (1976) introduce the Airline model, which is still routinely used for the modelling of economic seasonal time series. The Airline model is for a differenced time series (in levels and seasons) and constitutes a linear moving average of lagged Gaussian disturbances which depends on two coefficients and a fixed variance. In this paper a novel approach to seasonal adjustment is developed that is based on the Airline model and that accounts for outliers and breaks in time series. For this purpose we consider the canonical representation of the Airline model. It takes the model as a sum of trend, seasonal and irregular (unobserved) components which are uniquely identified as a result of the canonical decomposition. The resulting unobserved components time series model is extended by components that allow for outliers and breaks. When all components depend on Gaussian disturbances, the model can be cast in state space form and the Kalman filter can compute the exact log‐likelihood function. Related filtering and smoothing algorithms can be used to compute minimum mean squared error estimates of the unobserved components. However, the outlier and break components typically rely on heavy‐tailed densities such as the t or the mixture of normals. For this class of non‐Gaussian models, Monte Carlo simulation techniques will be used for estimation, signal extraction and seasonal adjustment. This robust approach to seasonal adjustment allows outliers to be accounted for, while keeping the underlying structures that are currently used to aid reporting of economic time series data. Copyright © 2006 John Wiley & Sons, Ltd.     

Chemical defense in the three European species ofCrematogaster ants

The composition of the Dufour gland of the antC. scutellaris has been reinvestigated by gas chromatography/mass spectrometry. The major components of the gland are (2E,5E,12Z)-4-oxoheneicosa-2,5,12-trien-1-ol acetate (1a) its ¹⁴ and ¹⁶ double bond isomers (1b and1c), and the corresponding (Z,Z)-dienes5a and5b, all containing an acetylated C₂₁ chain. The previously proposed structures1d, 1e, and5c, which are based on an homologous acetylated C₂₃ chain, correspond to minor derivatives present in the gland. Traces of acetylated C₁₉ homologs, tentatively identified as1g-1i, have also been found. The Dufour gland contents of the two other EuropeanCrematogaster species have also been studied.C. auberti is very similar toC. scutellaris in producing mainly1a, 1b and1c, together with the same higher and lower homologs, but it lacks the dienic derivatives5, whereasC. sordidula contains essentially the acetylated C₁₉ compounds1g, 1h, and1i, accompanied by acetylated C₁₇ homologs.     

Choosing among competing econometric forecasts: Regression‐based forecast combination using model selection

Forecast combination based on a model selection approach is discussed and evaluated. In addition, a combination approach based on ex ante predictive ability is outlined. The model selection approach which we examine is based on the use of Schwarz (SIC) or the Akaike (AIC) Information Criteria. Monte Carlo experiments based on combination forecasts constructed using possibly (misspecified) models suggest that the SIC offers a potentially useful combination approach, and that further investigation is warranted. For example, combination forecasts from a simple averaging approach MSE‐dominate SIC combination forecasts less than 25% of the time in most cases, while other ‘standard’ combination approaches fare even worse. Alternative combination approaches are also compared by conducting forecasting experiments using nine US macroeconomic variables. In particular, artificial neural networks (ANN), linear models, and professional forecasts are used to form real‐time forecasts of the variables, and it is shown via a series of experiments that SIC, t‐statistic, and averaging combination approaches dominate various other combination approaches. An additional finding is that while ANN models may not MSE‐dominate simpler linear models, combinations of forecasts from these two models outperform either individual forecast, for a subset of the economic variables examined. Copyright © 2001 John Wiley & Sons, Ltd.     

Exact test for opposite trends of probability changes in one or several 3×2 tables

Zusammenfassung Der «Likelihood»-Quotiententest wird auf einer 3×2-Kontigenztafel mit unbekannten Wahrscheinlichkeitenp _ij (i=1,2,3;j=1,2) angewandt, um die Hypothese H₀:p _i1=p _i2 (i=1,2,3) gegen die alternative Hypothese H₁:p ₁₁>p ₁₂ p ₃₁<p ₃₂ zuprüfen, und zwar wenn kleine Stichproben vorhanden sind. Ausserdem wird die Kombination solcher Tests behandelt. Als Beispiel wird diese Testtheorie beim Wahlverhalten des Kabeljaus im Dressurversuch über akustische Lokalisation in zwei Stimulussituationen verwendet.

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The close cooperation with Drs.E. Meelis, Institute of Theoretical Biology Leyden, The Netherlands, in applying the likelihood ratio test to this case is gratefully acknowledged.

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The author is greatly indebted to Dr.J. Oosterhoff, Mathematical Institute, University of Nijmegen, The Netherlands, for introducing the subclasses 1b and 1c in the computation of vector and for the explicit expressions in these cases which eliminated the need for a numerical optimization. Further more valuable remarks regarding the combination problem were obtained.     

Sopra un caso particolare della superficie F 4 (3) di M. Noether

Summary The Noetherian surfaceF ₄ ⁽³⁾ , which is represented on a plane by a linear ³ system ofC ₉(A ₁ ³ A ₂ ³ A ₃ ³ A ₄ ³ A ₅ ³ A ₆ ³ A ₇ ³ A ₈ ³ A ₉ ² A ₁₀), possesses generally only one linear pencil of elliptic cubics. IfA _i (i=1, 2, , 9) are the basis points of aHalphen pencil ofC ₉,A ₁₀ is infinitely near toA ₉, and in this caseF ₄ ⁽³⁾ is a not trivial example of such a surface with two pencils of elliptic cubics.     

Semiparametric forecast intervals

Consider forecasting the economic variable Y_t+h with predictors X _t, where h is the forecast horizon. This paper introduces a semiparametric method that generates forecast intervals of Y_t+h| X _t from point forecast models. First, the point forecast model is estimated, thereby taking advantage of its predictive power. Then, nonparametric estimation of the conditional distribution function (CDF) of the forecast error conditional on X _t builds the rest of the forecast distribution around the point forecast, from which symmetric and minimum‐length forecast intervals for Y_t+h| X _t can be constructed. Under mild regularity conditions, asymptotic analysis shows that (1) regardless of the quality of the point forecast model (i.e., it may be misspecified), forecast quantiles are consistent and asymptotically normal; (2) minimum length forecast intervals are consistent. Proposals for bandwidth selection and dimension reduction are made. Three sets of simulations show that for reasonable point forecast models the method has significant advantages over two existing approaches to interval forecasting: one that requires the point forecast model to be correctly specified, and one that is based on fully nonparametric CDF estimate of Y_t+h| X _t. An application to exchange rate forecasting is presented. Copyright © 2010 John Wiley & Sons, Ltd.     

Extracellular Mg2+ regulates intracellular Mg2+ and its subcellular compartmentation in fission yeast, Schizosaccharomyces pombe

Effects of extracellular magnesium ions ([Mg²⁺]_o ) on intracellular free Mg²⁺ ([Mg²⁺]_i ) and its subcellular distribution in single fission yeast cells, Schizosaccharomyces pombe, were studied with digital-imaging microscopy and an Mg²⁺ fluorescent probe (mag-fura-2). Using 0.44 mM [Mg²⁺]_o , [Mg²⁺]_i in yeast cells was 0.91±0.08 mM. Elevation of [Mg²⁺]_o to 1.97 mM induced rapid (within 5 min) increments in [Mg²⁺]_i (2.18±0.11 mM). Lowering [Mg²⁺]_o to 0.06 mM, however, exerted no significant effects on [Mg²⁺]_i (0.93±0.14 mM), at least for periods of up to 30 min. Irrespective of the [Mg²⁺]_o used, the subcellular distribution of [Mg²⁺]_i remained hetero geneous, i.e. where the sub-plasma membrane region >cytoplasm >nucleus. [Mg²⁺] in all three subcellular compartments increased significantly, two- to threefold, concomitant with [Mg²⁺]_i when placed in 1.97 mM [Mg²⁺]_o . We conclude that [Mg²⁺]_i in fission yeast is maintained at a physiologic level when [Mg²⁺]_o is low, but intracellular free Mg²⁺ rapidly rises when [Mg²⁺]_o is elevated. Like most eukaryotic cells, yeast may have a Mg²⁺ transport system(s) which functions to maintain gradients of Mg²⁺ from the outside to inside the cell and among its subcellular compartments. Received 18 April 1996; received after revision 4 July 1996; accepted 26 July 1996     

Composition du suc de décongélation du muscle strié de la grenouille

Summary Because of cell membrane destruction, fluid escaping a muscle on thawing contains a large amount of proteins (myogen and globulin X). Whilst usual gradientsa, b, andc are present in the fluid, the gradientsd ande also occurring in extracts of unstimulated frog muscles are replaced by the gradientx already found in extracts of in N₂ exhausted muscles.     

Cadmium-induced autophagy and apoptosis are mediated by a calcium signaling pathway

The cytotoxicity of cadmium (Cd) induced autophagy and apoptosis in MES-13 cells was determined by flow cytometry. Autophagy was also assessed by formation of autophagosomes and processing of LC3. Pharmacological inhibition of autophagy resulted in increased of cell viability, suggesting autophagy plays a role in cell death in Cd-treated mesangial cells. Cd also induced a rapid elevation in cytosolic calcium ([Ca²⁺]_i ), and modulation of [Ca²⁺]_i via treatment with IP ₃R inhibitor or knockdown of calcineurin resulted in a change in the proportion of cell death, suggesting that the release of calcium from the ER plays a crucial role in Cd-induced cell death. Inhibition of Cd-induced ERK activation by PD 98059 suppressed Cd-induced autophagy, and BAPTA-AM eliminated activation of ERK. BAPTA-AM also inhibited Cd-induced mitochondrial depolarization and activation of caspases. These findings demonstrated that Cd induces both autophagy and apoptosis through elevation of [Ca²⁺]_i, followed by Ca²⁺-ERK and Ca²⁺-mitochondria-caspase signaling pathways. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users. Received 05 July 2008; received after revision 25 August 2008; accepted 17 September 2008     

Phosphate transport inTrypanosoma cruzi

Zusammenfassung Epimastigoten vonTrypanosoma cruzi sind für Orthophosphate (P _i ) relativ undurchlässig. Man kann trotzdem bei zellen, die aus Ortophosphat armen Kulturen stammen, einen signifikanten Übertritt von Ortophosphat ins Zellinnere messen. Bei diesen Zellen ist die Geschwindigkeit des P _i -Transportes ins Zellinnere trotz eines diesem Vorgang entgegenwirkenden Phosphat-Konzentrationsgradienten etwa 5 mal grösser als die der P _i -Abgabe aus dem Zellinnern des umgebenden Mediums. Die Durchlässigkeitsschranke für P _i wird durch 3 mM Jodacetat zerstört.

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This work was supported by grants of Consejo Nacional de Investigaciones Científicas y Técnicas (Argentina), the Instituto Nacional de Farmacología, and the Wellcome Trust.     

Robust estimation of conditional variance of time series using density power divergences

Suppose Z _t is the square of a time series Y _t whose conditional mean is zero. We do not specify a model for Y _t , but assume that there exists a p ×1 parameter vector Φ such that the conditional distribution of Z _t | Z _{t ?1} is the same as that of , where Z _{t ?1}=(Z _{t ?1},…,Z _{t ?p} )^T for some lag p ?1. Consequently, the conditional variance of Y _t is some function of . To estimate Φ , we propose a robust estimation methodology based on density power divergences (DPD) indexed by a tuning parameter α ∈[0,1], which yields a continuum of estimators, , where α controls the trade‐off between robustness and efficiency of the DPD estimators. For each α , is shown to be strongly consistent. We develop data‐dependent criteria for the selection of optimal α and lag p in practice. We illustrate the usefulness of our DPD methodology via simulation studies for ARCH‐type models, where the errors are drawn from a gross‐error contamination model and the conditional variance is a linear and/or nonlinear function of . Furthermore, we analyze the Chicago Board Options Exchange Dow Jones volatility index data and show that our DPD approach yields viable models for the conditional variance, which are as good as, or superior to, ARCH/GARCH models and two other divergence‐based models in terms of in‐sample and out‐of‐sample forecasts.     

Estimating and forecasting the long‐memory parameter in the presence of periodicity

We consider one parametric and five semiparametric approaches to estimate D in SARFIMA (0, D, 0)_s processes, that is, when the process is a fractionally integrated ARMA model with seasonality s. We also consider h‐step‐ahead forecasting for these processes. We present the proof of some features of this model and also a study based on a Monte Carlo simulation for different sample sizes and different seasonal periods. We compare the different estimation procedures analyzing the bias, the mean squared error values, and the confidence intervals for the estimators. We also consider three different methods to choose the total number of regressors in the regression analysis for the semiparametric class of estimation procedures. We apply the methodology to the Nile River flow monthly data, and also to a simulated seasonal fractionally integrated time series. Copyright © 2007 John Wiley & Sons, Ltd.