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In this article, we aim to reconcile the interrelated role of social and spatial influences on colloquial German by conducting an apparent-time analysis of 15 lexical, morphological, and phonetic variables from the Atlas of Colloquial German (AdA). Specifically, we introduce a “change in variation intensity” (CVI) measure meant to gauge the degree of change in colloquial speech between younger and older cohorts. Using this measure, we investigate (a) whether the CVI within and across variables is prone to spatial patterns and (b) the extent to which the CVI differs systematically between variable types. Results from visual–spatial analyses indicate clear spatial patterns, though the geographical distributions are largely item-specific, and a linear mixed-effects model revealed no effect of variable type. More broadly, the CVI measure represents an important advancement in how we address language variation and change from a methodological-statistical perspective, specifically when dealing with heterogeneous, crowdsourced data.
Our goal is to show that both the fast and slow versions of the triangle map (a type of multi-dimensional continued fraction algorithm) in dimension n are ergodic, resolving a conjecture of Messaoudi, Noguiera, and Schweiger [Ergodic properties of triangle partitions. Monatsh. Math.157 (2009), 283–299]. This particular type of higher dimensional multi-dimensional continued fraction algorithm has recently been linked to the study of partition numbers, with the result that the underlying dynamics has combinatorial implications.
We consider a Poisson autoregressive process whose parameters depend on the past of the trajectory. We allow these parameters to take negative values, modelling inhibition. More precisely, the model is the stochastic process $(X_n)_{n\ge0}$ with parameters $a_1,\ldots,a_p \in \mathbb{R}$, $p\in\mathbb{N}$, and $\lambda \ge 0$, such that, for all $n\ge p$, conditioned on $X_0,\ldots,X_{n-1}$, $X_n$ is Poisson distributed with parameter $(a_1 X_{n-1} + \cdots + a_p X_{n-p} + \lambda)_+$. This process can be regarded as a discrete-time Hawkes process with inhibition and a memory of length p. In this paper we initiate the study of necessary and sufficient conditions of stability for these processes, which seems to be a hard problem in general. We consider specifically the case $p = 2$, for which we are able to classify the asymptotic behavior of the process for the whole range of parameters, except for boundary cases. In particular, we show that the process remains stochastically bounded whenever the solution to the linear recurrence equation $x_n = a_1x_{n-1} + a_2x_{n-2} + \lambda$ remains bounded, but the converse is not true. Furthermore, the criterion for stochastic boundedness is not symmetric in $a_1$ and $a_2$, in contrast to the case of non-negative parameters, illustrating the complex effects of inhibition.
It has become increasingly clear that economies can fruitfully be viewed as networks, consisting of millions of nodes (households, firms, banks, etc.) connected by business, social, and legal relationships. These relationships shape many outcomes that economists often measure. Over the past few years, research on production networks has flourished, as economists try to understand supply-side dynamics, default cascades, aggregate fluctuations, and many other phenomena. Economic Networks provides a brisk introduction to network analysis that is self-contained, rigorous, and illustrated with many figures, diagrams and listings with computer code. Network methods are put to work analyzing production networks, financial networks, and other related topics (including optimal transport, another highly active research field). Visualizations using recent data bring key ideas to life.
We construct an unfolding path in Outer space which does not converge in the boundary, and instead it accumulates on the entire 1-simplex of projectivized length measures on a nongeometric arational ${\mathbb R}$-tree T. We also show that T admits exactly two dual ergodic projective currents. This is the first nongeometric example of an arational tree that is neither uniquely ergodic nor uniquely ergometric.
We show that stationary time series can be uniformly approximated over all finite time intervals by mixing, non-ergodic, non-mean-ergodic, and periodic processes, and by codings of aperiodic processes. A corollary is that the ergodic hypothesis—that time averages will converge to their statistical counterparts—and several adjacent hypotheses are not testable in the non-parametric case. Further Baire category implications are also explored.
A comparison theorem for state-dependent regime-switching diffusion processes is established, which enables us to pathwise-control the evolution of the state-dependent switching component simply by Markov chains. Moreover, a sharp estimate on the stability of Markovian regime-switching processes under the perturbation of transition rate matrices is provided. Our approach is based on elaborate constructions of switching processes in the spirit of Skorokhod’s representation theorem varying according to the problem being dealt with. In particular, this method can cope with switching processes in an infinite state space and not necessarily of birth–death type. As an application, some known results on the ergodicity and stability of state-dependent regime-switching processes can be improved.
We start with quasi-invariant measures and early on, in the second section of this chapter, we introduce the powerful concept of the first return map. This concept, along with the concept of nice sets, forms our most fundamental tool in Part IV of our book, which is devoted to presenting a refined ergodic theory of elliptic functions. We introduce, in this chapter, the notions of ergodicity and conservativity (always satisfied for finite invariant measures), and prove the Poincaré Recurrence Theorem, Birkhoff Ergodic Theorem, and Hopf Ergodic Theorem, the last pertaining to infinite measures. We also provide a powerful, though perhaps somewhat neglected by the ergodic community, tool for proving the existence of invariant s-finite measures absolutely continuous with respect to given quasi-invariant measures.
In this chapter, we use the fruits of the, already proven, existence of Sullivan conformal measures with a minimal exponent and its various dynamical characterizations. Having compact nonrecurrence, we are able to prove in this chapter that this minimal exponent is equal to the Hausdorff dimension $\HD(J(f))$ of the Julia set $J(f)$, which we denote by $h$. We also obtain here some strong restrictions on the possible locations of atoms of such conformal measures. In the last section of this chapter, we culminate our work on Sullivan conformal measures for elliptic functions treated on their own. There and from then onward, we assume that our compactly nonrecurrent elliptic function is regular (we define this concept). For this class of elliptic functions, we prove the uniqueness and atomlessness of $h$-conformal measures along with their first fundamental stochastic properties such as ergodicity and conservativity.
We prove some estimates for the variations of transition probabilities of the (1+1)-affine process. From these estimates we deduce the strong Feller and the ergodic properties of the total variation distance of the process. The key strategy is the pathwise construction and analysis of several Markov couplings using strong solutions of stochastic equations.
In this paper, we study the ergodicity of the geodesic flows on surfaces with no focal points. Let M be a smooth connected and closed surface equipped with a $C^{\infty }$ Riemannian metric g, whose genus $\mathfrak {g} \geq 2$. Suppose that $(M,g)$ has no focal points. We prove that the geodesic flow on the unit tangent bundle of M is ergodic with respect to the Liouville measure, under the assumption that the set of points on M with negative curvature has at most finitely many connected components.
In a recent refreshing paper, Cowie (2022, The Philosophical Quarterly) analyses the hypothesis of artificial origin of the mysterious interstellar object 1I/2017 U1 ʻOumuamua, as well as the wider question of justification of the artefactual origin explanation for anomalous astronomical phenomena. This highly commendable philosophical project should be further developed in order to establish more general methodology for dealing with traces and manifestations of extraterrestrial intentional actors. In the present note, I demonstrate a couple of weaknesses of the standard account, mainly dealing with philosophy of technology, and suggest ways of improving upon it.
Nonlinear Markov chains with finite state space were introduced by Kolokoltsov (Nonlinear Markov Processes and Kinetic Equations, 2010). The characteristic property of these processes is that the transition probabilities depend not only on the state, but also on the distribution of the process. Here we provide first results regarding their invariant distributions and long-term behaviour: we show that under a continuity assumption an invariant distribution exists and provide a sufficient criterion for the uniqueness of the invariant distribution. Moreover, we present examples of peculiar limit behaviour that cannot occur for classical linear Markov chains. Finally, we present for the case of small state spaces sufficient (and easy-to-verify) criteria for the ergodicity of the process.
This chapter discusses the practice of measurement in psychological research. Here, where we cast doubt on the basic assumptions and endeavours underlying the act of measuring in mainstream psychology. Next, we introduce the processual alternative, which stresses the study of activity as situated and coupled with an environment. This chapter explains how a process approach to ‘measurement’ is thus fundamentally different from the standard one, and can remedy existing issues related to non-ergodicity and the ecological fallacy. These ideas are illustrated by means of the concept of intelligence, which is undoubtedly one of psychology’s show-pieces of measurement.
We provide constructions of age-structured branching processes without or with immigration as pathwise-unique solutions to stochastic integral equations. A necessary and sufficient condition for the ergodicity of the model with immigration is also given.
We prove the convergence and ergodicity of a wide class of real and higher-dimensional continued fraction algorithms, including folded and $\alpha $-type variants of complex, quaternionic, octonionic, and Heisenberg continued fractions, which we combine under the framework of Iwasawa continued fractions. The proof is based on the interplay of continued fractions and hyperbolic geometry, the ergodicity of geodesic flow in associated modular manifolds, and a variation on the notion of geodesic coding that we refer to as geodesic marking. As a corollary of our study of markable geodesics, we obtain a generalization of Serret’s tail-equivalence theorem for almost all points. The results are new even in the case of some real and complex continued fractions.
This chapter gives a short summary of mathematical instruments required to model sensor systems in the presence of both deterministic and random processes. The concepts are organized in a compact overview for a more rapid consultation, emphasizing the convergences between different contexts.
We generalize the greedy and lazy $\beta $-transformations for a real base $\beta $ to the setting of alternate bases ${\boldsymbol {\beta }}=(\beta _0,\ldots ,\beta _{p-1})$, which were recently introduced by the first and second authors as a particular case of Cantor bases. As in the real base case, these new transformations, denoted $T_{{\boldsymbol {\beta }}}$ and $L_{{\boldsymbol {\beta }}}$ respectively, can be iterated in order to generate the digits of the greedy and lazy ${\boldsymbol {\beta }}$-expansions of real numbers. The aim of this paper is to describe the measure-theoretical dynamical behaviors of $T_{{\boldsymbol {\beta }}}$ and $L_{{\boldsymbol {\beta }}}$. We first prove the existence of a unique absolutely continuous (with respect to an extended Lebesgue measure, called the p-Lebesgue measure) $T_{{\boldsymbol {\beta }}}$-invariant measure. We then show that this unique measure is in fact equivalent to the p-Lebesgue measure and that the corresponding dynamical system is ergodic and has entropy $({1}/{p})\log (\beta _{p-1}\cdots \beta _0)$. We give an explicit expression of the density function of this invariant measure and compute the frequencies of letters in the greedy ${\boldsymbol {\beta }}$-expansions. The dynamical properties of $L_{{\boldsymbol {\beta }}}$ are obtained by showing that the lazy dynamical system is isomorphic to the greedy one. We also provide an isomorphism with a suitable extension of the $\beta $-shift. Finally, we show that the ${\boldsymbol {\beta }}$-expansions can be seen as $(\beta _{p-1}\cdots \beta _0)$-representations over general digit sets and we compare both frameworks.
Under a suitable bunching condition, we establish that stable holonomies inside center-stable manifolds for $C^{1+\beta }$ diffeomorphisms are uniformly bi-Lipschitz and, in fact, $C^{1+\mathrm {H}\ddot{\rm o}\mathrm {lder}}$. This verifies the ergodicity of suitably center-bunched, essentially accessible, partially hyperbolic $C^{1+\beta }$ diffeomorphisms and verifies that the Ledrappier–Young entropy formula holds for $C^{1+\beta }$ diffeomorphisms of compact manifolds.
We focus on the population dynamics driven by two classes of truncated $\alpha$-stable processes with Markovian switching. Almost necessary and sufficient conditions for the ergodicity of the proposed models are provided. Also, these results illustrate the impact on ergodicity and extinct conditions as the parameter $\alpha$ tends to 2.