scholarly journals Net reductions or spatiotemporal displacement of intentional wildfires in response to arrests? Evidence from Spain

2019 ◽  
Vol 28 (6) ◽  
pp. 397 ◽  
Author(s):  
Jeffrey P. Prestemon ◽  
David T. Butry ◽  
María L. Chas-Amil ◽  
Julia M. Touza
Keyword(s):  
Count Data ◽  
Meteorological Factors ◽  
Election Cycle ◽  
Count Models ◽  
Socioeconomic Variables ◽  
Space And Time ◽  
Subsequent Time ◽  
Time Periods ◽  
Environmental Crimes

Research to date has not examined how the impacts of arrests manifest across space and time in environmental crimes. We evaluate whether arrests reduce or merely spatiotemporally displace intentional illegal outdoor firesetting. Using municipality-level daily wildfire count data from Galicia, Spain, from 1999 to 2014, we develop daily spatiotemporal ignition count models of agricultural, non-agricultural and total intentional illegal wildfires as functions of spatiotemporally lagged arrests, the election cycle, seasonal and day indicators, meteorological factors and socioeconomic variables. We find evidence that arrests reduce future intentional illegal fires across space in subsequent time periods.

Understanding Distressed Residential Transaction Discounts Across Price Segments and Market Conditions

2020 ◽  
Vol 42 (1) ◽  
pp. 151-182
Author(s):  
Ramya Rajajagadeesan Aroul ◽  
J. Andrew Hansz ◽  
Mauricio Rodriguez
Keyword(s):  
Transaction Costs ◽  
Time Varying ◽  
Market Segment ◽  
Market Conditions ◽  
Large Market ◽  
Space And Time ◽  
Wide Range ◽  
Time Periods ◽  
Market Areas

In the literature, there is a wide range of discounts associated with foreclosures. Comparisons across studies are difficult as they use different methodologies across large areas over different time periods. We employ a consistent methodology across space and time. We find modest discounts, within the range of typical transaction costs, in all but the highest priced market segment. Higher priced segments could explain prior findings of substantial discounts. We find that discounts are time-varying, with discounts increasing with market distress. A one-size-fits-all approach is not appropriate when estimating distressed transaction discounts across large market areas or under changing market conditions.

scholarly journals Approaching the Unification and Diversity of Pottery Assemblages

2020 ◽  
Vol 47 ◽  
pp. 522-535
Author(s):  
Aleksandr Diachenko ◽  
Iwona Sobkowiak-Tabaka ◽  
Sergej Ryzhov
Keyword(s):  
Complex Systems ◽  
Dynamic Behaviour ◽  
Subsequent Time ◽  
Time Periods ◽  
Ceramic Assemblages ◽  
Tripolye Culture

This paper questions the cycling nature of the unification and diversity of pottery forms through a case study of ceramics of the Western Tripolye culture in the Southern Bug and Dnieper interfluve in modern Ukraine. We identified the cultural cycle representing the transition from more unified ceramic assemblages to more diverse ones, and then back to more unified assemblages. This cultural cycle is disturbed by the increase in the diversity of pottery sets at three of ten subsequent time periods we have analysed. The obtained results are discussed in frames of deterministic explanations and the dynamic behaviour of complex systems.

scholarly journals Associations between author-level metrics in subsequent time periods

2021 ◽  
Vol 15 (4) ◽  
pp. 101218
Author(s):  
Ana C.M. Brito ◽  
Filipi N. Silva ◽  
Diego R. Amancio
Keyword(s):  
Subsequent Time ◽  
Time Periods

Graffiti Content as an Index of Political Interest

1975 ◽  
Vol 40 (2) ◽  
pp. 616-618 ◽  
Author(s):  
Dale O. Jorgenson ◽  
Charles Lange
Keyword(s):  
College Campus ◽  
The Other ◽  
Political Interest ◽  
National Elections ◽  
Subsequent Time ◽  
Time Periods

Graffiti in 25 male restrooms on a college campus were examined for political references on the eve of the 1972 national elections and at three subsequent time periods. As predicted, the proportion of “political” content in the graffiti was significantly greater on the eve of the election than at any of the other periods.

scholarly journals A Stochastic Condensation Mechanism for Inducing Underdispersion in Count Models

2021 ◽  
Author(s):  
Chenangnon Frédéric Tovissodé ◽  
Romain Glele Kakai
Keyword(s):  
Negative Binomial Distribution ◽  
Count Data ◽  
Negative Binomial ◽  
Count Models ◽  
Original Variable ◽  
Binomial Distributions ◽  
Original Distribution ◽  
Count Distribution ◽  
Special Cases ◽  
Stochastic Mechanism

It is quite easy to stochastically distort an original count variable to obtain a new count variable with relatively more variability than in the original variable. Many popular overdispersion models (variance greater than mean) can indeed be obtained by mixtures, compounding or randomlystopped sums. There is no analogous stochastic mechanism for the construction of underdispersed count variables (variance less than mean), starting from an original count distribution of interest. This work proposes a generic method to stochastically distort an original count variable to obtain a new count variable with relatively less variability than in the original variable. The proposed mechanism, termed condensation, attracts probability masses from the quantiles in the tails of the original distribution and redirect them toward quantiles around the expected value. If the original distribution can be simulated, then the simulation of variates from a condensed distribution is straightforward. Moreover, condensed distributions have a simple mean-parametrization, a characteristic useful in a count regression context. An application to the negative binomial distribution resulted in a distribution allowing under, equi and overdispersion. In addition to graphical insights, fields of applications of special cases of condensed Poisson and condensed negative binomial distributions were pointed out as an indication of the potential of condensation for a flexible analysis of count data

Sound and the Comic/Horror Romance Film

2020 ◽  
pp. 245-259
Author(s):  
Janet Staiger
Keyword(s):  
Multidimensional Approach ◽  
Television Series ◽  
Critical Approach ◽  
Comparative Analyses ◽  
Space And Time ◽  
Hollywood Films ◽  
Critical Activity ◽  
Time Periods ◽  
The 1960S

Media scholars (and audiences) routinely make useful comparative analyses of films and television series. The problems of grouping texts are well known. This essay proposes a multidimensional approach to this critical activity, one that focuses on formulas, affects, and inflections. Narrative formulas and affects propel our sense of a genre; however, inflections such as stars, target audiences, locales, time periods, verisimilitude, taste markers, or performance styles can radically twist the base into something more complicated. One of the most important sorts of inflections is use of sound: aural effects, voice, and music. Such a multidimensional approach to grouping texts helps to resolve many anomalies in genre categorizing: for instance, the generic category of the musical. Scholars have tended to describe the musical based on Hollywood films created between 1930 and 1960. During this period, most musicals use a standard romance formula and vary the space and time to form several common “subgenres.” The author argues that, from the 1960s, artists begin to turn to other narrative formulas such as the male quest story (Tommy), horror (Sweeney Todd), the fallen-man melodrama (All That Jazz, Pennies from Heaven), and the bio pix (Hamilton). What the musical “is” is inflecting a narrative formula with a particular musical treatment—bursting into song or dance not necessarily provoked by a reasonably motivated diegetic event such as a nightclub act. Such an inflection of musical treatment could be applied to any narrative formula and has been. This essay explores this argument focusing on the comic/horror romance film Zombieland (2009) but with other examples to illustrate the viability of the critical approach and the functions of sound.

Variations in the Retail Price of Chemists' Goods: Testing Spatial and Structural Hypotheses and the ‘Sample of One’

1982 ◽  
Vol 14 (11) ◽  
pp. 1509-1522 ◽  
Author(s):  
T O'Connor ◽  
A J Parker
Keyword(s):  
Direct Relationship ◽  
Residential Area ◽  
Spatial Variations ◽  
Retail Price ◽  
Temporal Consistency ◽  
Multiple Correlation ◽  
Single Time ◽  
Subsequent Time ◽  
Time Period ◽  
Time Periods

Spatial variations in the price of chemists' goods in Dublin are examined for a number of different baskets of products and for two time periods, so as to tackle the problem of the ‘sample of one’. A number of hypotheses including measures of store size, proximity of competition, and the type of residential area in which the shop is located are examined by means of bivariate and multiple correlation in relation to price variations, and in general the results are consistent for different baskets at a single time period: shops which are expensive for one combination of products tend to be expensive for most product combinations. However, there is little consistency of results between the two time periods, and this must create problems for price-motivated consumers: an inexpensive shop at one time period may not necessarily be inexpensive at a subsequent time period even for the same products. Even so, there is some temporal consistency in that the size of shop generally has a direct relationship with variations in prices, smaller shops being the more expensive.

scholarly journals Very-Short-Term Power Prediction for PV Power Plants Using a Simple and Effective RCC-LSTM Model Based on Short Term Multivariate Historical Datasets

Electronics ◽  
2020 ◽  
Vol 9 (2) ◽  
pp. 289 ◽  
Author(s):  
Biaowei Chen ◽  
Peijie Lin ◽  
Yunfeng Lai ◽  
Shuying Cheng ◽  
Zhicong Chen ◽  
...  
Keyword(s):  
Power Generation ◽  
Power Plants ◽  
Meteorological Factors ◽  
Training Dataset ◽  
Percentage Error ◽  
Short Term ◽  
Similar Time ◽  
Proposed Model ◽  
Time Periods ◽  
Pv Power Generation

Improving the accuracy of very-short-term (VST) photovoltaic (PV) power generation prediction can effectively enhance the quality of operational scheduling of PV power plants, and provide a reference for PV maintenance and emergency response. In this paper, the effects of different meteorological factors on PV power generation as well as the degree of impact at different time periods are analyzed. Secondly, according to the characteristics of radiation coordinate, a simple radiation classification coordinate (RCC) method is proposed to classify and select similar time periods. Based on the characteristics of PV power time-series, the selected similar time period dataset (include power output and multivariate meteorological factors data) is reconstructed as the training dataset. Then, the long short-term memory (LSTM) recurrent neural network is applied as the learning network of the proposed model. The proposed model is tested on two independent PV systems from the Desert Knowledge Australia Solar Centre (DKASC) PV data. The proposed model achieving mean absolute percentage error of 2.74–7.25%, and according to four error metrics, the results show that the robustness and accuracy of the RCC-LSTM model are better than the other four comparison models.

On Difference Equations, Probability Models and the “Generalized Event Count” Distribution

1996 ◽  
Vol 6 ◽  
pp. 175-212 ◽  
Author(s):  
Timothy W. Amato
Keyword(s):  
Difference Equations ◽  
Count Data ◽  
Negative Binomial ◽  
Probability Model ◽  
Dispersion Parameter ◽  
Probability Models ◽  
Statistical Structure ◽  
Count Models ◽  
Count Distribution ◽  
The Common

In this article, the mathematical and probabilistic foundations of Gary King's “generalized event count” (GEC) model for dealing with unequally dispersed event count data are explored. It is shown that the GEC model is a probability model that joins together the binomial, negative binomial, and Poisson distributions. Some aspects of the GEC's reparameterization are described and extended and it is shown how different reparameterizations lead to different interpretations of the dispersion parameter. The common mathematical and statistical structure of “unequally dispersed” event count models as models that require estimation of the “number of trials” parameter along with the “probability” component is derived. Some questions pertaining to estimation of this class of models are raised for future discussion.

Sign in / Sign up

Export Citation Format

Share Document