Peter M. Robinson
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View article: Go hard or go home: Major removal of woody vegetation and sediment greatly enhances wetland plant and water beetle diversity recovery in a farmland pond landscape
Go hard or go home: Major removal of woody vegetation and sediment greatly enhances wetland plant and water beetle diversity recovery in a farmland pond landscape Open
Ponds are important habitats for biodiversity conservation and ecosystem service provisions in farmland settings. Agricultural intensification and cessation of traditional management have resulted in a substantial loss of open‐canopy farml…
View article: Dynamic Maximal Matching in Clique Networks
Dynamic Maximal Matching in Clique Networks Open
We consider the problem of computing a maximal matching with a distributed algorithm in the presence of batch-dynamic changes to the graph topology. We assume that a graph of $n$ nodes is vertex-partitioned among $k$ players that communica…
View article: Tight Bounds on the Message Complexity of Distributed Tree Verification
Tight Bounds on the Message Complexity of Distributed Tree Verification Open
We consider the message complexity of verifying whether a given subgraph of the communication network forms a tree with specific properties both in the KT-$ρ$ (nodes know their $ρ$-hop neighborhood, including node IDs) and the KT-$0$ (node…
View article: Computing Minimal Boolean Models of Gene Regulatory Networks
Computing Minimal Boolean Models of Gene Regulatory Networks Open
This is the implementation of the method described in the manuscript, and the LateX source
View article: The Climber-Tether Interface of the Space Elevator
The Climber-Tether Interface of the Space Elevator Open
The conditions at the interface between the space elevator tether and its climber determine the requirements of the tether material and the climber design. Graphene super-laminate was found to have sufficient tensile strength to support th…
View article: Improved Tradeoffs for Leader Election
Improved Tradeoffs for Leader Election Open
We consider leader election in clique networks, where $n$ nodes are connected by point-to-point communication links. For the synchronous clique under simultaneous wake-up, i.e., where all nodes start executing the algorithm in round $1$, w…
View article: What Can We Compute in a Single Round of the Congested Clique?
What Can We Compute in a Single Round of the Congested Clique? Open
We show that any one-round algorithm that computes a minimum spanning tree (MST) in the unicast congested clique must use a link bandwidth of $Ω(\log^3 n)$ bits in the worst case. Consequently, computing an MST under the standard assumptio…
View article: Byzantine-Resilient Counting in Networks
Byzantine-Resilient Counting in Networks Open
We present two distributed algorithms for the {\em Byzantine counting problem}, which is concerned with estimating the size of a network in the presence of a large number of Byzantine nodes. In an $n$-node network ($n$ is unknown), our fir…
View article: Nonparametric panel data regression with parametric cross-sectional dependence
Nonparametric panel data regression with parametric cross-sectional dependence Open
Summary In this paper, we consider efficiency improvement in a nonparametric panel data model with cross-sectional dependence. A generalised least squares (GLS)-type estimator is proposed by taking into account this dependence structure. P…
View article: Het-node2vec: second order random walk sampling for heterogeneous multigraphs embedding
Het-node2vec: second order random walk sampling for heterogeneous multigraphs embedding Open
Many real-world problems are naturally modeled as heterogeneous graphs, where nodes and edges represent multiple types of entities and relations. Existing learning models for heterogeneous graph representation usually depend on the computa…
View article: The Local Information Cost of Distributed Graph Spanners
The Local Information Cost of Distributed Graph Spanners Open
We introduce the \emph{local information cost} (LIC), which quantifies the amount of information that nodes in a network need to learn when solving a graph problem. We show that the local information cost presents a natural lower bound on …
View article: ESTIMATION FOR DYNAMIC PANEL DATA WITH INDIVIDUAL EFFECTS
ESTIMATION FOR DYNAMIC PANEL DATA WITH INDIVIDUAL EFFECTS Open
The article discusses statistical inference in parametric models for panel data. The models feature dynamics of a general nature, individual effects, and possible explanatory variables. The focus is on large-cross-section inference on Gaus…
View article: Leader Election in Well-Connected Graphs
Leader Election in Well-Connected Graphs Open
In this paper, we look at the problem of randomized leader election in synchronous distributed networks with a special focus on the message complexity. We provide an algorithm that solves the implicit version of leader election (where non-…
View article: Long-Range Dependent Curve Time Series
Long-Range Dependent Curve Time Series Open
We introduce methods and theory for functional or curve time series with long-range dependence. The temporal sum of the curve process is shown to be asymptotically normally distributed, the conditions for this covering a functional version…
View article: Identifying Cointegration by Eigenanalysis
Identifying Cointegration by Eigenanalysis Open
We propose a new and easy-to-use method for identifying cointegrated components of nonstationary time series, consisting of an eigenanalysis for a certain nonnegative definite matrix. Our setting is model-free, and we allow the integer-val…
View article: Adaptive Estimation in Multiple Time Series With Independent Component Errors
Adaptive Estimation in Multiple Time Series With Independent Component Errors Open
This article develops statistical methodology for semiparametric models for multiple time series of possibly high dimension N . The objective is to obtain precise estimates of unknown parameters (which characterize autocorrelations and cro…
View article: A Time- and Message-Optimal Distributed Algorithm for Minimum Spanning\n Trees
A Time- and Message-Optimal Distributed Algorithm for Minimum Spanning\n Trees Open
This paper presents a randomized Las Vegas distributed algorithm that\nconstructs a minimum spanning tree (MST) in weighted networks with optimal (up\nto polylogarithmic factors) time and message complexity. This algorithm runs in\n$\\tild…
View article: Central limit theorems for long range dependent spatial linear processes
Central limit theorems for long range dependent spatial linear processes Open
Central limit theorems are established for the sum, over a spatial region, of observations from a linear process on a $d$-dimensional lattice. This region need not be rectangular, but can be irregularly-shaped. Separate results are establi…
View article: Central limit theorems for long range dependent spatial linear processes
Central limit theorems for long range dependent spatial linear processes Open
Central limit theorems are established for the sum, over a spatial region, of observations from a linear process on a $d$-dimensional lattice. This region need not be rectangular, but can be irregularly-shaped. Separate results are establi…
View article: Series estimation under cross-sectional dependence
Series estimation under cross-sectional dependence Open
An asymptotic theory is developed for series estimation of nonparametric and semiparametric regression models for cross-sectional data under conditions on disturbances that allow for forms of cross-sectional dependence and heterogeneity, i…
View article: Identifying Cointegration by Eigenanalysis
Identifying Cointegration by Eigenanalysis Open
We propose a new and easy-to-use method for identifying cointegrated components of nonstationary time series, consisting of an eigenanalysis for a certain non-negative definite matrix. Our setting is model-free, and we allow the integer-va…
View article: Refinements in maximum likelihood inference on spatial autocorrelation in panel data
Refinements in maximum likelihood inference on spatial autocorrelation in panel data Open
In a panel data model with fixed effects, possible cross-sectional dependence is investigated in a spatial autoregressive setting. An Edgeworth expansion is developed for the maximum likelihood estimate of the spatial correlation coefficie…
View article: Fire in the woods or fire in the boiler: Implementing rural district heating to reduce wildfire risks in the forest–urban interface
Fire in the woods or fire in the boiler: Implementing rural district heating to reduce wildfire risks in the forest–urban interface Open
Many rural communities in British Columbia (western Canada) are at risk from wildfire. This risk will increase over time as a result of climate change because of higher average temperatures, longer growing seasons, and more intense drought…
View article: Panel nonparametric regression with fixed effects
Panel nonparametric regression with fixed effects Open
Nonparametric regression is developed for data with both a temporal and a cross-sectional dimension. The model includes additive, unknown, individual-specific components and allows also for cross-sectional and temporal dependence and condi…
View article: Gracefully Degrading Consensus and $k$-Set Agreement in Directed Dynamic\n Networks
Gracefully Degrading Consensus and $k$-Set Agreement in Directed Dynamic\n Networks Open
We study distributed agreement in synchronous directed dynamic networks,\nwhere an omniscient message adversary controls the availability of\ncommunication links. We prove that consensus is impossible under a message\nadversary that guaran…
View article: Inference on higher-order spatial autoregressive models with increasingly many parameters
Inference on higher-order spatial autoregressive models with increasingly many parameters Open
This paper develops consistency and asymptotic normality of parameter estimates for a higher-order spatial autoregressive model whose order, and number of regressors, are allowed to approach infinity slowly with sample size. Both least squ…