Real space renormalization group for twisted lattice N=4 super Yang-Mills

A necessary ingredient for our previous results on the form of the long distance effective action of the twisted lattice N=4 super Yang-Mills theory is the existence of a real space renormalization group which preserves the lattice structure, both the symmetries and the geometric interpretation of the fields. In this brief article we provide an explicit example of such a blocking scheme and illustrate its practicality in the context of a small scale Monte Carlo renormalization group calculation. We also discuss the implications of this result, and the possible ways in which to use it in order to obtain further information about the long distance theory.Comment: 15 pages, 3 figure

Profile morphology and polarization of young pulsars

We present polarization profiles at 1.4 and 3.1 GHz for 14 young pulsars with characteristic ages less than 75 kyr. Careful calibration ensures that the absolute position angle of the linearly polarized radiation at the pulsar is obtained. In combination with previously published data we draw three main conclusions about the pulse profiles of young pulsars. (1) Pulse profiles are simple and consist of either one or two prominent components. (2) The linearly polarized fraction is nearly always in excess of 70 per cent. (3) In profiles with two components the trailing component nearly always dominates, only the trailing component shows circular polarization and the position angle swing is generally flat across the leading component and steep across the trailing component. Based on these results we can make the following generalisations about the emission beams of young pulsars. (1) There is a single, relatively wide cone of emission from near the last open field lines. (2) Core emission is absent or rather weak. (3) The height of the emission is between 1 and 10 per cent of the light cylinder radius.Comment: Accepted for publication in MNRAS. 16 page

Uniform confidence bands for functions estimated nonparametrically with instrumental variables

This paper is concerned with developing uniform confidence bands for functions estimated nonparametrically with instrumental variables. We show that a sieve nonparametric instrumental variables estimator is pointwise asymptotically normally distributed. The asymptotic normality result holds in both mildly and severely ill-posed cases. We present an interpolation method to obtain a uniform confidence band and show that the bootstrap can be used to obtain the required critical values. Monte Carlo experiments illustrate the finite-sample performance of the uniform confidence band. This paper is a revised version of CWP18/09.

Semiparametric estimation of a panel data proportional hazards model with fixed effects

This paper considers a panel duration model that has a proportional hazards specification with fixed effects. The paper shows how to estimate the baseline and integrated baseline hazard functions without assuming that they belong to known, finitedimensional families of functions. Existing estimators assume that the baseline hazard function belongs to a known parametric family. Therefore, the estimators presented here are more general than existing ones. This paper also presents a method for estimating the parametric part of the proportional hazards model with dependent right censoring, under which the partial likelihood estimator is inconsistent. The paper presents some Monte Carlo evidence on the small sample performance of the new estimators.

Uniform confidence bands for functions estimated nonparametrically with instrumental variables

This paper is concerned with developing uniform confidence bands for functions estimated nonparametrically with instrumental variables. We show that a sieve nonparametric instrumental variables estimator is pointwise asymptotically normally distributed. The asymptotic normality result holds in both mildly and severely ill-posed cases. We present an interpolation method to obtain a uniform confidence band and show that the bootstrap can be used to obtain the required critical values. Monte Carlo experiments illustrate the finite-sample performance of the uniform confidence band.

Nonparametric estimation of an additive quantile regression model

This paper is concerned with estimating the additive components of a nonparametric additive quantile regression model. We develop an estimator that is asymptotically normally distributed with a rate of convergence in probability of n-r/(2r+1) when the additive components are r-times continuously differentiable for some r = 2. This result holds regardless of the dimension of the covariates and, therefore, the new estimator has no curse of dimensionality. In addition, the estimator has an oracle property and is easily extended to a generalized additive quantile regression model with a link function. The numerical performance and usefulness of the estimator are illustrated by Monte Carlo experiments and an empirical example.

Nonparametric instrumental variables estimation of a quantile regression model

We consider nonparametric estimation of a regression function that is identified by requiring a specified quantile of the regression "error" conditional on an instrumental variable to be zero. The resulting estimating equation is a nonlinear integral equation of the first kind, which generates an ill-posed-inverse problem. The integral operator and distribution of the instrumental variable are unknown and must be estimated nonparametrically. We show that the estimator is mean-square consistent, derive its rate of convergence in probability, and give conditions under which this rate is optimal in a minimax sense. The results of Monte Carlo experiments show that the estimator behaves well in finite samples.Statistical inverse, endogenous variable, instrumental variable, optimal rate, nonlinear integral equation, nonparametric regression

Testing a parametric quantile-regression model with an endogenous explanatory variable against a nonparametric alternative

This paper is concerned with inference about a function g that is identified by a conditional quantile restriction involving instrumental variables. The paper presents a test of the hypothesis that g belongs to a finite-dimensional parametric family against a nonparametric alternative. The test is not subject to the ill-posed inverse problem of nonparametric instrumental variables estimation. Under mild conditions, the test is consistent against any alternative model. In large samples, its power is arbitrarily close to 1 uniformly over a class of alternatives whose distance from the null hypothesis is O ( n1/2 ), where n is the sample size. Monte Carlo simulations illustrate the finite-sample performance of the test.Hypothesis test, quantile estimation, instrumental variables, specification

Probes of nearly conformal behavior in lattice simulations of minimal walking technicolor

We present results from high precision, large volume simulations of the lattice gauge theory corresponding to minimal walking technicolor. We find evidence that the pion decay constant vanishes in the infinite volume limit and that the dependence of the chiral condensate on quark mass m_q is inconsistent with spontaneous symmetry breaking. These findings are consistent with the all-orders beta function prediction as well as the Schroedinger functional studies that indicate the existence of a nontrivial infrared fixed point.Comment: 16 pages, 3 figure