Nonlinear Error Correction Models.

The relationship between cointegration and error correction (EC) models is well characterized in a linear context, but the extension to the nonlinear context is still a challenge. Few extensions of the linear framework have been done in the context of nonlinear error correction (NEC) or asymmetric and time varying error correction models. In this paper, we propose a theoretical framework based on the concept of near epoch dependence (NED) that allows us to formally address these issues. In particular, we partially extend the Granger Representation Theorem to the nonlinear case.

Nuclear PDFs from neutrino deep inelastic scattering

We study nuclear effects in charged current deep inelastic neutrino-iron scattering in the frame-work of a chi^2 analysis of parton distribution functions. We extract a set of iron PDFs and show that under reasonable assumptions it is possible to constrain the valence, light sea and strange quark distributions. Our iron PDFs are used to compute x_{Bj}-dependent and Q^2-dependent nuclear correction factors for iron structure functions which are required in global analyses of free nucleon PDFs. We compare our results with nuclear correction factors from neutrino-nucleus scattering models and correction factors for charged lepton-iron scattering. We find that, except for very high x_{Bj}, our correction factors differ in both shape and magnitude from the correction factors of the models and charged-lepton scattering.Comment: 25 pages, 10 figures; minor updates to match published versio

Asymmetric and time-varying error-correction: an application to labour demand in the UK

In this paper we compare the asymmetric and time-varying error-correction models that have recently been proposed, and apply these to the case of UK aggregate labour demand. The aim of the paper is to investigate the possible co-existence of time-varying adjustment on the one hand, and constant asymmetric error-correction on the other hand. We find that without allowing for time-varying adjustment variables, the asymmetric error-correction models of Granger and Lee (1989) and Escribano (1986) work well. But once the time-varying adjustment variables are included, the evidence for time-invariant asymmetric adjustment is marginal

Multiple testing correction in linear mixed models.

BackgroundMultiple hypothesis testing is a major issue in genome-wide association studies (GWAS), which often analyze millions of markers. The permutation test is considered to be the gold standard in multiple testing correction as it accurately takes into account the correlation structure of the genome. Recently, the linear mixed model (LMM) has become the standard practice in GWAS, addressing issues of population structure and insufficient power. However, none of the current multiple testing approaches are applicable to LMM.ResultsWe were able to estimate per-marker thresholds as accurately as the gold standard approach in real and simulated datasets, while reducing the time required from months to hours. We applied our approach to mouse, yeast, and human datasets to demonstrate the accuracy and efficiency of our approach.ConclusionsWe provide an efficient and accurate multiple testing correction approach for linear mixed models. We further provide an intuition about the relationships between per-marker threshold, genetic relatedness, and heritability, based on our observations in real data

Evaluating Alternative Methods of Forecasting House Prices: A Post-Crisis Reassessment

This paper compares the performance of different forecasting models of California house prices. Multivariate, theory-driven models are able to outperform a theoretical time series models across a battery of forecast comparison measures. Error correction models were best able to predict the turning point in the housing market, whereas univariate models were not. Similarly, even after the turning point occurred, error correction models were still able to outperform univariate models based on MSFE, bias, and forecast encompassing statistics and tests. These results highlight the importance of incorporating theoretical economic relationships into empirical forecasting models.house prices, forecasting, forecast comparison, forecast encompassing

Analysis of quantum error correction with symmetric hypergraph states

Graph states have been used to construct quantum error correction codes for independent errors. Hypergraph states generalize graph states, and symmetric hypergraph states have been shown to allow for the correction of correlated errors. In this paper, it is shown that symmetric hypergraph states are not useful for the correction of independent errors, at least for up to 30 qubits. Furthermore, error correction for error models with protected qubits is explored. A class of known graph codes for this scenario is generalized to hypergraph codes.Comment: 18 pages, 2 figures; corrected number of figures; 16.02.2018: removed minor inconsistencies in font choice, added supplemental files 23.02.2018: added journal re

Innovation in prediction planning for anterior open bite correction

This study applies recent advances in 3D virtual imaging for application in the prediction planning of dentofacial deformities. Stereo-photogrammetry has been used to create virtual and physical models, which are creatively combined in planning the surgical correction of anterior open bite. The application of these novel methods is demonstrated through the surgical correction of a case