A seasonal periodic long memory model for monthly river flows

Based on simple time series plots and periodic sample autocorrelations, we document that monthly river flow data display long memory, in addition to pronounced seasonality. In fact, it appears that the long memory characteristics vary with the season. To describe these two properties jointly, we propose a seasonal periodic long memory model and fit it to the well-known Fraser river data (to be obtained from Statlib at http://lib.stat.cmu.edu/datasets/. We provide a statistical analysis and provide impulse response functions to show that shocks in certain months of the year have a longer lasting impact than those in other months

A periodic long memory model for quarterly UK inflation

We consider an extension of the fractionally integrated ARIMA(0, d, 0) model for quarterly UK inflation, where we allow the fractional integration parameter d to vary with the season s. This periodic ARFIMA(0, d, 0) model does not only provide an informative in-sample description, it may also be useful for out-of-sample forecasting. The main result is that the integration parameter in the first two quarters is significantly larger than that in the last two quarters

Did men of taste and civilization save the stage? Theatre-going in Rotterdam, 1860-1916. A statistical analysis of ticket sales

This essay deals with Dutch theater history of the second half of the 19th century (1860—1916). It statistically tests, whether the dominant opinion in Dutch theater writing, that after 1870 the stage recovered from a half century of decline, due to a renewed interest in it by the city elite, occupying the first ranks with a taste for civilized modern drama, and that, hence, a sharp cleft became visible between lower-rank tastes and upper-rank tastes. We test the tenability of this position on the basis of the Rotterdam Grand Theater archives, which contain ticket sales per rank per performance from 1776 till 1916, and the play bills of the performances. We analyze aggregated behavior of an anonymous theater consumers subdivided into price classes, hypothesizing that differences in attendance to high and low quality plays (as the critics judged them) over the different ranks, might reveal class-based divisions of taste. A long-memory time series analysis confirms that there is a significant gradual change of quality in the theater during the period 1860—1881, but this change is hardly rank- (and by implication likely class-) based. A second time series analysis, analyzing the impact of the repertoire and companies controlled for season and dynamics of the time series over the years 1860—1887 and 1887—1916, hardly sustains the narrative of recovery for most products as related to ranks. Only in a few telling instances, there was a clear opposition between low-rank tastes and upper-rank tastes. Hence, the recovery thesis must on the whole be rejected. This research will be followed-up by a prosopographical analysis of season-ticket and coupon holders in the Rotterdam theaters from 1773—1916, in which more detailed information on the social backgrounds and particularly on social class division of not anonymous theater audiences in `the long 19th century' is central

Inflation, Forecast Intervals and Long Memory Regression Models

We examine recursive out-of-sample forecasting of monthly postwar U.S. core inflation and log price levels. We use the autoregressive fractionally integrated moving average model with explanatory variables (ARFIMAX). Our analysis suggests a significant explanatory power of leading indicators associated with macroeconomic activity and monetary conditions for forecasting horizons up to two years. Even after correcting for the effect of explanatory variables, there is conclusive evidence of both fractional integration and structural breaks in the mean and variance of inflation in the 1970s and 1980s and we incorporate these breaks in the forecasting model for the 1980s and 1990s. We compare the results of the fractionally integrated ARFIMA(0,d,0) model with those for ARIMA(1,d,1) models with fixed order of d=0 and d=1 for inflation. Comparing mean squared forecast errors, we find that the ARMA(1,1) model performs worse than the other models over our evaluation period 1984-1999. The ARIMA(1,1,1) model provides the best forecasts, but its multi-step forecast intervals are too large

Development of a recombinant antibody to target peptides and proteins to sialoadhesin-expressing macrophages

Background: Sialoadhesin (Sn)-expressing monocytes/macrophages have been associated with several diseases like inflammatory and autoimmune disorders as well as viral infections, and they also appear to play a role in the initiation of an adaptive immune response. This makes Sn-expressing cells not only attractive targets for cell-directed therapies, but also an appealing target for vaccination. Furthermore, since Sn was shown to be an endocytic receptor, the conjugation of effector molecules to an Sn-specific ligand should allow intracellular delivery of these conjugates. Previously, we developed functional Sn-specific immunoconjugates that were generated via chemical coupling. Although successful, the system requires significant optimization for each immunoconjugate to be made. To generate a more flexible and controlled system, we developed a recombinant antibody vector allowing the creation of genetic antibody fusion constructs. This paper reports on the characterization of the recombinant antibody and the evaluation of its use for Sn-directed targeting. Results: The variable domains of the porcine Sn-specific monoclonal antibody 41D3 were sequenced and cloned in frame with a mouse IgG1 backbone. Transfection of HEK293T cells with the resulting plasmid led to the secretion of fully assembled IgG into the culture medium. This recombinant antibody rec41D3 was shown to specifically bind to porcine Sn with a comparable affinity as the native monoclonal antibody. In addition, rec41D3 also induced Sn endocytosis in primary macrophages and resided for prolonged times in early/late endosomes. To allow the generation of antibody fusion constructs, a multiple cloning site was introduced at the C-terminus of the heavy chain. Two fusion constructs were generated, one containing a V5 peptide tag and one containing an eGFP molecule. Both constructs were shown to be efficiently produced in HEK293T cells and easily purified using standard protein G chromatography. In addition, both V5 and eGFP were shown to be co-internalized together with rec41D3 into Sn-expressing primary macrophages. Conclusions: A recombinant antibody allowing targeted delivery of peptides and proteins to Sn-expressing macrophages was developed. Production and purification of antibody fusion constructs was possible without major optimization and with batch to batch consistency, confirming the development of a versatile antibody vector to evaluate Sn-directed targeting strategies in a porcine animal model

On periodic correlations between estimated seasonal and nonseasonal components for US and German unemployment

The orthogonality assumption of seasonal and nonseasonal components for official quarterly unemployment figures in Germany and the US is examined. Although nonperiodic correlations do not seem to reject the orthogonality assumption, a periodic analysis based on correlation functions that vary with the seasons indicates the violation of orthogonality. The unadjusted data can be described by periodic autoregressive models with a unit root. In simulations, the empirical findings for the German data are replicated, where simple models are used to generate artificial samples. Multivariate seasonal adjustment leads to large periodic correlations. Additive adjustment leads to smaller ones