Analysis of residential property sales using space–time point patterns

2017 ◽  
Vol 21 ◽  
pp. 149-165 ◽  
Author(s):  
Lucia Paci ◽  
María Asunción Beamonte ◽  
Alan E. Gelfand ◽  
Pilar Gargallo ◽  
Manuel Salvador
Keyword(s):  
Space Time ◽  
Residential Property ◽  
Point Patterns ◽  
Property Sales ◽  
Time Point

Travelling in Time: How to Wholly Exist in Two Places at the Same Time

2006 ◽  
Vol 36 (3) ◽  
pp. 309-334 ◽  
Author(s):  
Kristie Miller
Keyword(s):  
Time Travel ◽  
Space Time ◽  
Additional Advantage ◽  
Spatial Locations ◽  
Time Point

It is possible to wholly exist at multiple spatial locations at the same time. At least, if time travel is possible and objects endure, then such must be the case. To accommodate this possibility requires the introduction of a spatial analog of either relativising properties to times — relativising properties to spatial locations — or of relativising the manner of instantiation to times — relativising the manner of instantiation to spatial locations. It has been suggested, however, that introducing irreducibly spatially relativised or spatially adverbialised properties presents some difficulties for the endurantist. I will consider an objection according to which embracing such spatially relativised properties could lead us to reject mereology altogether in favour of a metaphysics according to which objects are wholly present at every space-time point at which they exist. I argue that although such a view is coherent, there are some good reasons to reject it. Moreover, I argue that the endurantist can introduce spatially relativised or adverbialised properties without conceding that objects lack spatial parts. Such a strategy has the additional advantage that it allows the endurantist not only to explain time travel, but also to reconcile our competing intuitions about cases of fission.

scholarly journals S-money: virtual tokens for a relativistic economy

2019 ◽  
Vol 475 (2225) ◽  
pp. 20190170 ◽  
Author(s):  
Adrian Kent
Keyword(s):  
Data Storage ◽  
Relevant Information ◽  
Space Time ◽  
User Privacy ◽  
Standard Quantum ◽  
Bit Commitment ◽  
Time Points ◽  
Security Questions ◽  
Time Point

We propose definitions and implementations of ‘S-money’—virtual tokens designed for high-value fast transactions on networks with relativistic or other trusted signalling constraints, defined by inputs that in general are made at many network points, some or all of which may be space-like separated. We argue that one significant way of characterizing types of money in space–time is via the ‘summoning’ tasks they can solve: that is, how flexibly the money can be propagated to a desired space–time point in response to relevant information received at various space–time points. We show that S-money is more flexible than standard quantum or classical money in the sense that it can solve deterministic summoning tasks that they cannot. It requires the issuer and user to have networks of agents with classical data storage and communication, but no long-term quantum state storage, and is feasible with current technology. User privacy can be incorporated by secure bit commitment and zero-knowledge proof protocols. The level of privacy feasible in given scenarios depends on efficiency and composable security questions that remain to be systematically addressed.

MMAE-Based Control with Space-Time Point Process Observations

1985 ◽  
Vol AES-21 (3) ◽  
pp. 292-300 ◽  
Author(s):  
Peter Maybeck ◽  
William Zicker
Keyword(s):  
Point Process ◽  
Space Time ◽  
Time Point

An Application of Space-Time Analysis to Improve the Epidemiological Understanding of the Papaya-Papaya Yellow Crinkle Pathosystem

2007 ◽  
Vol 8 (1) ◽  
pp. 65
Author(s):  
Paul D. Esker ◽  
Karen S. Gibb ◽  
Philip M. Dixon ◽  
Forrest W. Nutter
Keyword(s):  
Strong Evidence ◽  
Pattern Analysis ◽  
Space Time ◽  
Point Pattern Analysis ◽  
Point Pattern ◽  
Incidence Data ◽  
Time Interaction ◽  
Spatio Temporal ◽  
Time Point ◽  
Contagion Process

Yellow crinkle disease of papaya is a serious threat to papaya production in Australia. Space-time point pattern analysis was used to study the spatial and temporal dependence of two phytoplasma strains that cause yellow crinkle: tomato big bud (TBB) and sweet potato little leaf V4 (SPLL-V4). Incidence data for both phytoplasma strains were obtained from a field study conducted in Katherine, NT, Australia, between January 1996 and May 1999. The primary ecological and epidemiological question of interest was to elucidate the scale of spatial or spatio-temporal aggregation of phytoplasma-infected papaya plants. The hypothesis was that there would be a contagion process, where TBB- and SPLL-V4-infected papaya would be aggregated and not random. To test this hypothesis, a point pattern spatial analysis using Monte Carlo simulation was initially applied to the incidence data. Results of this analysis suggested that SPLL-V4 infected papaya plants displayed aggregation with spatial dependence up to 30 m (10 to 15 plants along or across rows), whereas there was not strong evidence to suggest that TBB-infected papaya plants were aggregated. However, when a space-time point pattern analysis was subsequently used to simultaneously test for the interaction between space and time, there was strong evidence (P < 0.01 for SPLL-V4 and P < 0.10 for TBB) to suggest a space-time interaction for both SPLL-V4 and TBB. For SPLL-V4, a space-time risk window of approximately 10 months and 20 m was detected, whereas for TBB, this risk window was 5 months and 10 m. The results of these studies support the hypothesis that papaya infection by both phytoplasma strains appears to be the result of a contagion process, providing support for the contention that insect vectors are the most likely mechanism for acquisition, dispersal, and transmission. Accepted for publication 26 April 2007. Published 26 July 2007.

Forward likelihood-based predictive approach for space-time point processes

2011 ◽  
Vol 22 (6) ◽  
pp. 749-757 ◽  
Author(s):  
Marcello Chiodi ◽  
Giada Adelfio
Keyword(s):  
Point Processes ◽  
Space Time ◽  
Predictive Approach ◽  
Time Point
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