A unified approach to nonlinearity, structural change and outliers

This paper demonstrates that the class of conditionally linear and Gaussian state-space models offers a general and convenient framework for simultaneously handling nonlinearity, structural change and outliers in time series. Many popular nonlinear time series models, including threshold, smooth transition and Markov-Switching models, can be written in state-space form. It is then straightforward to add components that capture parameter instability and intervention effects. We advocate a Bayesian approach to estimation and inference, using an efficient implementation of Markov Chain Monte Carlo sampling schemes for such linear dynamic mixture models. The general modelling framework and the Bayesian methodology are illustrated by means of several examples. An application to quarterly industrial production growth rates for the G7 countries demonstrates the empirical usefulness of the approach

The Quantity Theory of Money is Valid. The New Keynesians are Wrong!

We test the quantity theory of money (QTM) using a novel approach and a large new sample. We do not follow the usual approach of first differentiating the logarithm of the Cambridge equation to obtain an equation relating the growth rate of real GDP, the growth rate of money and inflation. These variables must then again be ‘integrated’ by averaging in order to obtain stable relationships. Instead we suggest a much simpler procedure for testing directly the stability of the coefficient of the Cambridge equation. For 125 countries and post-war data we find the coefficient to be surprisingly stable. We do not select for high inflation episodes as was done in most empirical studies; inflation rates do not even appear in our data set. Much work supporting the QTM has been done by economic historians and at the University of Chicago by Milton Friedman and his associates. The QTM was a foundation stone of the monetarist revolution. Subsequently belief in it waned. The currently dominant New Keynesian School, implicitly or explicitly denies the validity of the QTM. We survey this history and argue that the QTM is valid and New Keynesians are wrong

Shower Thoughts: Why Scientists Should Spend More Time in the Rain

Stormwater is a vital resource and dynamic driver of terrestrial ecosystem processes. However, processes controlling interactions during and shortly after storms are often poorly seen and poorly sensed when direct observations are substituted with technological ones. We discuss how human observations complement technological ones and the benefits of scientists spending more time in the storm. Human observation can reveal ephemeral storm-related phenomena such as biogeochemical hot moments, organismal responses, and sedimentary processes that can then be explored in greater resolution using sensors and virtual experiments. Storm-related phenomena trigger lasting, oversized impacts on hydrologic and biogeochemical processes, organismal traits or functions, and ecosystem services at all scales. We provide examples of phenomena in forests, across disciplines and scales, that have been overlooked in past research to inspire mindful, holistic observation of ecosystems during storms. We conclude that technological observations alone are insufficient to trace the process complexity and unpredictability of fleeting biogeochemical or ecological events without the shower thoughts produced by scientists\u27 human sensory and cognitive systems during storms

Diversity and Functional Traits of Lichens in Ultramafic Areas: A Literature Based Worldwide Analysis Integrated by Field Data at the Regional Scale

While higher plant communities found on ultramafics are known to display peculiar characteristics, the distinguishability of any peculiarity in lichen communities is still a matter of contention. Other biotic or abiotic factors, rather than substrate chemistry, may contribute to differences in species composition reported for lichens on adjacent ultramafic and non-ultramafic areas. This work examines the lichen biota of ultramafics, at global and regional scales, with reference to species-specific functional traits. An updated world list of lichens on ultramafic substrates was analyzed to verify potential relationships between diversity and functional traits of lichens in different Köppen–Geiger climate zones. Moreover, a survey of diversity and functional traits in saxicolous communities on ultramafic and non-ultramafic substrates was conducted in Valle d’Aosta (North-West Italy) to verify whether a relationship can be detected between substrate and functional traits that cannot be explained by other environmental factors related to altitude. Analyses (unweighted pair group mean average clustering, canonical correspondence analysis, similarity-difference-replacement simplex approach) of global lichen diversity on ultramafic substrates (2314 reports of 881 taxa from 43 areas) displayed a zonal species distribution in different climate zones rather than an azonal distribution driven by the shared substrate. Accordingly, variations in the frequency of functional attributes reflected reported adaptations to the climate conditions of the different geographic areas. At the regional scale, higher similarity and lower species replacement were detected at each altitude, independent from the substrate, suggesting that altitude-related climate factors prevail over putative substrate–factors in driving community assemblages. In conclusion, data do not reveal peculiarities in lichen diversity or the frequency of functional traits in ultramafic areas

Potential role and chronology of abnormal expression of the Deleted in Colon Cancer (DCC) and the p53 proteins in the development of gastric cancer

BACKGROUND: Loss of activity of tumor suppressor genes is considered a fundamental step in a genetic model of carcinogenesis. Altered expression of the p53 and the Deleted in Colon Cancer (DCC) proteins has been described in gastric cancer and this event may have a role in the development of the disease. According to this hypothesis, we investigated the p53 and the DCC proteins expression in different stages of gastric carcinomas. METHODS: An immunohistochemical analysis for detection of p53 and DCC proteins expression was performed in tumor tissue samples of patients with UICC stage I and II gastric cancer. For the purpose of the analysis, the staining results were related to the pathologic data and compared between stage categories. RESULTS: Ninety-four cases of gastric cancer were analyzed. Disease stage categories were pT1N0 in 23 cases, pT2N0 in 20 cases, pT3N0 in 20 cases and pT1-3 with nodal involvment in 31 cases. Stage pT1-2N0 tumors maintained a positive DCC expression while it was abolished in pT3N0 tumors (p <.001). A significant higher proportion of patients with N2 nodal involvement showed DCC negative tumors. In muscular-invading tumors (pT2-3N0) the majority of cases showed p53 overexpression, whereas a significantly higher proportion of cases confined into the mucosa (pT1N0) showed p53 negative tumors. Also, a higher frequency of p53 overexpression was detected in cases with N1 and N2 metastatic lymphnodal involvement. CONCLUSIONS: Altered expression of both DCC and p53 proteins is detectable in gastric carcinomas. It seems that loss of wild-type p53 gene function and consequent p53 overexpression may be involved in early stages of tumor progression while DCC abnormalities are a late event

Nonparametric Regression Density Estimation Using Smoothly Varying Normal Mixtures

We model a regression density nonparametrically so that at each value of the covariates the density is a mixture of normals with the means, variances and mixture probabilities of the components changing smoothly as a function of the covariates. The model extends existing models in two important ways. First, the components are allowed to be heteroscedastic regressions as the standard model with homoscedastic regressions can give a poor fit to heteroscedastic data, especially when the number of covariates is large. Furthermore, we typically need a lot fewer heteroscedastic components, which makes it easier to interpret the model and speeds up the computation. The second main extension is to introduce a novel variable selection prior into all the components of the model. The variable selection prior acts as a self adjusting mechanism that prevents overfitting and makes it feasible to fit high dimensional nonparametric surfaces. We use Bayesian inference and Markov Chain Monte Carlo methods to estimate the model. Simulated and real examples are used to show that the full generality of our model is required to fit a large class of densities

Measurement of the CP-violating phase ϕs and the Bs0 meson decay width difference with Bs0 → J/ψϕ decays in ATLAS

A measurement of the Bs0 decay parameters in the Bs0 → J/ψϕ channel using an integrated luminosity of 14.3 fb−1 collected by the ATLAS detector from 8 TeV pp collisions at the LHC is presented. The measured parameters include the CP -violating phase ϕs, the decay width Γs and the width difference between the mass eigenstates ΔΓs. The values measured for the physical parameters are statistically combined with those from 4.9 fb−1 of 7 TeV data, leading to the following: ϕ s =−0.090±0.078(stat.)±0.041(syst.)rad ΔΓ s =0.085±0.011(stat.)±0.007(syst.)ps −1 Γ s =0.675±0.003(stat.)±0.003(syst.)ps −1 In the analysis the parameter ΔΓs is constrained to be positive. Results for ϕs and ΔΓs are also presented as 68% and 95% likelihood contours in the ϕs-ΔΓs plane. Also measured in this decay channel are the transversity amplitudes and corresponding strong phases. All measurements are in agreement with the Standard Model predictions