90,492 research outputs found
Range Unit Root (RUR) Tests: Robust against Nonlinearities, Error Distributions, Structural Breaks and Outliers
No full textSince the seminal paper by Dickey and Fuller in 1979, unit-root tests have conditioned the standard approaches to analysing time series with strong serial dependence in mean behaviour, the focus being placed on the detection of eventual unit roots in an autoregressive model fitted to the series. In this paper, we propose a completely different method to test for the type of long-wave patterns observed not only in unit-root time series but also in series following more complex data-generating mechanisms. To this end, our testing device analyses the unit-root persistence exhibited by the data while imposing very few constraints on the generating mechanism. We call our device the range unit-root (RUR) test since it is constructed from the running ranges of the series from which we derive its limit distribution. These nonparametric statistics endow the test with a number of desirable properties, the invariance to monotonic transformations of the series and the robustness to the presence of important parameter shifts. Moreover, the RUR test outperforms the power of standard unit-root tests on near-unit-root stationary time series; it is invariant with respect to the innovations distribution and asymptotically immune to noise. An extension of the RUR test, called the forward?backward range unit-root (FB-RUR) improves the check in the presence of additive outliers. Finally, we illustrate the performances of both range tests and their discrepancies with the Dickey?Fuller unit-root test on exchange rate series.Publicad
Root developmental responses to heterogeneous water and nitrogen supply
No full textBetter understanding of the interaction between the soil physical properties determining water and nitrate availability and the root proliferation and gene expression components of nutrient acquisition could contribute to food security, but may have been limited by experimental systems.
A sand rhizotron system was developed to investigate Arabidopsis (Arabidopsis thaliana) root responses to altered water and nitrate supply as manipulated by soil physical properties. When this system was compared to agar, root disparities were explained by differences in hydraulic properties, highlighting the importance of the soil physical component. The sand rhizotron system was adopted to quantify root proliferation and gene expression responses to altered water and nitrate availability in wild-type and selected mutant seedlings.
In the sand rhizotron system, primary root length and lateral root density were oppositely regulated by water availability, but similarly independent of nitrate supply. The expression of the nitrate transporter AtNRT2.1 and the aquaporin AtPIP2.2 was coordinated across all treatments. Their concentration-dependent hydraulic regulation was confirmed for AtNRT2.1 by in situ imaging of a Green Fluorescent Protein reporter line. AtNAR2.1 and AtNRT2.1 expression demonstrated independent responses to water and nitrate availability despite the requirement of AtNAR2.1 for AtNRT2.1 uptake function. Root proliferation responses to water availability under high (10.0 mM) nitrate were lost in the atnar2.1 mutant and coincided with altered hormone-associated gene (AtEIN2, AtABI4 and AtIPT5) expression. Root proliferation and AtNAR2.1 responses to water availability under high (10.0 mM) nitrate required AtPIP2.2. The coordination of root proliferation and gene expression responses to altered water and nitrate availability is proposed, that includes novel roles for AtNRT2.1, AtNAR2.1 and AtPIP2.2
Search for the rare decay D+ -> D(0)e(+)nu(e)
No full textKolcu, Onur Buğra (Arel Author)Using a data set with an integrated luminosity of 2.93 fb(-1) collected at root s = 3.773 GeV with the BESIII detector operating at the BEPCII storage rings, we search for the rare decay D+ -> D(0)e(+)nu(e). No signal events are observed. We set the upper limit on the branching fraction for D+ -> D(0)e(+)nu(e) to be 1.0 x 10(-4) at the 90% confidence level
A range unit root test
No full textSince the seminal paper by Dickey and Fuller in 1979, unit-root tests have conditioned the standard approaches to analyse time series with strong serial dependence, the focus being placed in the detection of eventual unit roots in an autorregresive model fitted to the series. In this paper we propose a completely different method to test for the type of long-wave patterns observed not only in unit root time series but also in series following more complex data generating mechanisms. To this end, our testing device analyses the trend exhibit by the data, without imposing any constraint on the generating mechanism. We call our device the Range Unit Root (RUR) Test since it is constructed from running ranges of the series. These statistics allow a more general characterization of a strong serial dependence in the mean behavior, thus endowing our test with a number of desirable properties, among which its error-model-free asymptotic distribution, the invariance to nonlinear monotonic transformations of the series and the robustness to the presence of level shifts and additive outliers. In addition, the RUR test outperforms the power of standard unit root tests on near-unit-root stationary time series and is asymptotically immune to noise
Root traits for infertile soils
No full textThis work was supported by the Rural and Environment Science and Analytical Services Division (RESAS) of the Scottish Government through Workpackage 3.3 (2011–2016)Crop production is often restricted by the availability of essential mineral elements. For example, the availability of N, P, K, and S limits low-input agriculture, the phytoavailability of Fe, Zn, and Cu limits crop production on alkaline and calcareous soils, and P, Mo, Mg, Ca,and K deficiencies, together with proton, Al and Mn toxicities, limit crop production on acid soils. Since essential mineral elements are acquired by the root system, the development of crop genotypes with root traits increasing their acquisition should increase yields on infertile soils. This paper examines root traits likely to improve the acquisition of these elements and observes that, although the efficient acquisition of a particular element requires a specific set of root traits, suites of traits can be identified that benefit the acquisition of a group of mineral elements. Elements can be divided into three Groups based on common trait requirements. Group 1 comprises N, S, K, B, and P. Group 2 comprises Fe, Zn, Cu, Mn, and Ni. Group 3 contains mineral elements that rarely affect crop production. It is argued that breeding for a limited number of distinct root ideotypes,addressing particular combinations of mineral imbalances, should be pursued.Peer reviewe
Measurements of the absolute branching fractions for D-s(+) -> eta e(+)nu(e) and D-s(+) -> eta ' e(+)nu(e)
No full textBy analyzing 482 pb(-1) of e(+)e(-) collision data collected at root s = 4.009 GeV with the BESIII detector at the BEPCII collider, we measure the absolute branching fractions for the semileptonic decays D-s(+) -> eta e(+)nu(e) and D-s(+) -> eta ' e(+)nu(e) to be B(D-s(+) -> eta e(+)nu(e)) = (2.30 +/- 0.31 +/- 0.08)% and B(D-s(+) -> eta ' e(+)nu(e)) = (0.93 +/- 0.30 +/- 0.05)%, respectively, and their ratio B(D-s(+) -> eta ' e(+)nu(e)) / B(D-s(+) -> eta ' e(+)nu(e)) = 0.40 +/- 0.14 +/- 0.02, where the first uncertainties are statistical and the second ones are systematic. The results are in good agreement with previous measurements within uncertainties; they can be used to determine the eta-eta' mixing angle and improve upon the D-s(+) semileptonic branching ratio precision
Range unit root tests
No full textSince the seminal paper by Dickey and Fuller in 1979, unit-root tests have conditioned the standard approaches to analyse time series with strong serial dependence, the focus being placed in the detection of eventual unit roots in an autorregresive model fitted to the series. In this paper we propose a completely different method to test for the type of "long-wave" patterns observed not only in unit root time series but also in series following more complex data generating mechanism. To this end, our testing device analyses the trend exhibit by the data, without imposing any constraint on the generating mechanism. We call our device the Range Unit Root (RUR) Test since it is constructed from running ranges of the series. These statistics allow a more general characterization of a strong serial dependence in the mean behavior, thus endowing our test with a number of desirable properties. Among these properties are the invariance to nonlinear monotonic transformations of the series and the robustness to the presence of level shifts and additive outliers. In addition, the RUR test outperforms the power of standard unit root tests on near-unit-root stationary time series
A decision theoretic analysis of the unit root hypothesis using mixtures of elliptical models
No full textTime Series;Unit Root
Threshold stochastic unit root models
No full textThis paper introduces a new class of stochastic unit root (STUR) processes, where the randomness of the autorregresive unit root is driven by a threshold variable. These new models, the threshold autorregresive stochastic unit root (TARSUR) models, are stationary in some regimes and mildly explosive in others. TARSUR models are not only an alternative to fixed unit root models but present interpretation, estimation and testing advantages with
respect to the existent STUR models. The paper analyzes the stationarity properties of
the TARSUR models and proposes a simple t -statistic for testing the null hypothesis of a fixed unit root versus a stochastic unit root hypothesis. It is shown that its asymptotic distribution (AD) depends on the knowledge we have about the threshold values: known, unknown but identified, and unknown and unidentified. In the first two cases the AD is a standard Normal distribution, while in the last one the AD is a functional of Brownian Motions and Brownian Sheets. Monte Carlo simulations show that the proposed tests behave very well in finite samples and that the Dickey-Fuller test cannot easily distinguish
between an exact unit root and a threshold stochastic unit root. The paper concludes with applications to stock prices and interest rates where the hypothesis of a fixed unit root is rejected in favor of the threshold stochastic unit root
Estimation in threshold autoregressive models with a stationary and a unit root regime
No full textThis paper treats estimation in a class of new nonlinear threshold autoregressive models with both a stationary and a unit root regime. Existing literature on nonstationary threshold models have basically focused on models where the nonstationarity can be removed by differencing and/or where the threshold variable is stationary. This is not the case for the process we consider, and nonstandard estimation problems are the result. This paper proposes a parameter estimation method for such nonlinear threshold autoregressive models using the theory of null recurrent Markov chains. Under certain assumptions, we show that the ordinary least squares (OLS) estimators of the parameters involved are asymptotically consistent. Furthermore, it can be shown that the OLS estimator of the coefficient parameter involved in the stationary regime can still be asymptotically normal while the OLS estimator of the coefficient parameter involved in the nonstationary regime has a nonstandard asymptotic distribution. In the limit, the rate of convergence in the stationary regime is asymptotically proportional to n-1/4, whereas it is n-1 in the nonstationary regime. The proposed theory and estimation method are illustrated by both simulated data and a real data example.Autoregressive process; null-recurrent process; semiparametric model; threshold time series; unit root structure.
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