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Search indexed arXiv papers on artificial intelligence, large language models, computer vision and robotics. Read source abstracts and follow links to arXiv.

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At least 37 records · Page 2Linked to original sources
arXiv2011

Böögg Bang drives global climate change

The Böögg is a large model of a snowman, constructed of inflammable materials and filled with explosives. During the traditional festival of Sechseläuten, which takes place each spring in Zurich, Switzerland, the Böögg is placed atop a wooden pyre, which is set alight. According to popular legend, the time that elapses until the Böögg's head explodes (the "head-bang" time) is said to give a rough forecast of local weather conditions prevailing during the following summer. However, recent research has questioned the validity of this prediction. To study the Böögg's predictive powers, we analyzed the Böögg head-bang time record from 1965-2010 within the context of global climate change. Our analysis shows that the Böögg head-bang time is a good predictor not of short-term local weather, as might be expected from the legend, but of the behavior of the entire global climate system.

physics.pop-ph↗
arXiv2011

Baby Morse Theory in Data Analysis

A methodology is proposed for inferring the topology underlying point cloud data. The approach employs basic elements of Morse Theory, and is capable of producing not only a point estimate of various topological quantities (e.g., genus), but it can also assess their sampling uncertainty in a probabilistic fashion. Several examples of point cloud data in three dimensions are utilized to demonstrate how the method yields interval estimates for the topology of the data as a 2-dimensional surface embedded in R^3.

stat.OT↗
arXiv2011

A flexible observed factor model with separate dynamics for the factor volatilities and their correlation matrix

Our article considers a regression model with observed factors. The observed factors have a flexible stochastic volatility structure that has separate dynamics for the volatilities and the correlation matrix. The correlation matrix of the factors is time-varying and its evolution is described by an inverse Wishart process. The model specifies the evolution of the observed volatilities flexibly and is particularly attractive when the dimension of the observations is high. A Markov chain Monte Carlo algorithm is developed to estimate the model. It is straightforward to use this algorithm to obtain the predictive distributions of future observations and to carry out model selection. The model is illustrated and compared to other Wishart-type factor multivariate stochastic volatility models using various empirical data including monthly stock returns and portfolio weighted returns. The evidence suggests that our model has better predictive performance. The paper also allows the idiosyncratic errors to follow individual stochastic volatility processes in order to deal with more volatile data such as daily or weekly stock returns.

stat.OT↗
arXiv2011

Cooperative spectrum sensing over unreliable reporting channel

This article aims to analyze a cooperative spectrum sensing scheme using a centralized approach with unreliable reporting channel. The spectrum sensing is applied to a cognitive radio system, where each cognitive radio performs a simple energy detection and send the decision to a fusion center through a reporting channel. When the decisions are available at the fusion center, a n-out-of-K rule is applied. The impact of the choice of the parameter n in the cognitive radio system performance is analyzed in the case where the reporting channel introduces errors.

stat.OT↗
arXiv2011

A Markov Chain approach to determine the optimal performance period and bad definition for credit scorecard

Performance period determination and bad definition for credit scorecard has been a mix of fortune for the typical data modeler. The lack of literature on these matters led to a proliferation of approaches and techniques to solve the problems. However, the most commonly accepted approach involves subjective interpretations of the performance period and bad definition as well as being chicken and egg problem. These complications result in poorly developed credit scorecard with minimal benefits to the banks. In this paper, we will be recommending a simple and effective approach to resolve these issues.

stat.AP↗
arXiv2011

Some notes on biasedness and unbiasedness of two-sample Kolmogorov-Smirnov test

This paper deals with two-sample Kolmogorov-Smirnov test and its biasedness. This test is not unbiased in general in case of different sample sizes. We found out most biased distribution for some values of significance level $α$. Moreover we discovered that there exists number of observation and significance level $α$ such that this test is unbiased at level $α$.

stat.OT↗
arXiv2011

Revealing Sub-Optimality Conditions of Strategic Decisions

Conceptual view of fitness and fitness measurement of strategic decisions on information systems, technological systems and innovation are becoming more important in recent years. This paper determines some dynamics of fitness landscape which are lead to termination of decision makers' research before reaching the global maximum in strategic decisions. These dynamics are specified according to management decision making models and supported with simulation results. This article determines simulation results by means of "Fitness Value" and "Probability of Optimality". Correlation between these two concepts may be remarkable according to revealing optimal values in innovative and research-based decision making approaches beside sub-optimal results of traditional decision making approaches.

stat.OT↗
arXiv2011

Which are the best cities for psychology research worldwide? A map visualizing city ratios of observed and expected numbers of highly-cited papers

We present scientometric results about world-wide centers of excellence in psychology. Based on Web of Science data, domain-specific excellence can be identified for cities where highly cited papers are published. Data refer to all psychology articles published in 2007 which are documented in the Social Science Citation Index and to their citation frequencies from 2007 to May 2011. Visualized are 214 cities with an article output of at least 50 in 2007. Statistical z tests are used for the evaluation of the degree to which an observed number of top-cited papers (top-10%) for a city differs from the number expected on the basis of randomness in the selection of papers. Map visualizing city ratios on significant differences between observed and expected numbers of highly-cited papers point at excellence centers in cities at the East and West Coast of the United States as well as in Great Britain, Germany, the Netherlands, Ireland, Belgium, Sweden, Finland, Australia, and Taiwan. Furthermore, positive but non-significant differences in favor of high citation rates are documented for some cities in the United States, Great Britain, the Netherlands, the Scandinavian and the German-speaking countries, Belgium, France, Spain, Israel, South Korea, and China. Scientometric results show convincingly that highly-cited psychological research articles come from the Anglo-American countries and some of the non-English European countries in which the number of English-language publications has increased during the last decades.

stat.OT↗
arXiv2011

Boundary detection in disease mapping studies

In disease mapping, the aim is to estimate the spatial pattern in disease risk over an extended geographical region, so that areas with elevated risks can be identified. A Bayesian hierarchical approach is typically used to produce such maps, which models the risk surface with a set of spatially smooth random effects. However, in complex urban settings there are likely to be boundaries in the risk surface, which separate populations that are geographically adjacent but have very different risk profiles. Therefore this paper proposes an approach for detecting such risk boundaries, and tests its effectiveness by simulation. Finally, the model is applied to lung cancer incidence data in Greater Glasgow, Scotland, between 2001 and 2005.

stat.OT↗
arXiv2011

Order preserving property of moment estimators

Balakrishnan and Mi [1] considered order preserving property of maximum likelihood estimators. In this paper there are given conditions under which the moment estimators have the property of preserving stochastic orders. There is considered property of preserving for usual stochastic order as well as for likelihood ratio order. Mainly, sufficient conditions are given for one parameter family of distributions and also for exponential family, location family and scale family.

math.ST↗
arXiv2026

High dimensional Bayesian inference for Gaussian directed acyclic graph models

We study centered Gaussian models Markov with respect to a directed acyclic graph (DAG) whose vertices have a fixed parent ordering. We construct a conjugate family on the modified Cholesky parameters, with one shape parameter per vertex, and derive its induced distributions on incomplete covariance and precision coordinates. The distribution is proper exactly when \(α_i>|\mathrm{pa}(i)|+2\) for every vertex, and its nodewise conditional-variance and regression parameters are independent across vertices. This factorization gives a closed-form normalizing constant, conjugate updating, marginal likelihoods, and explicit full-matrix posterior means. We distinguish these posterior means from nonlinear completions of incomplete-coordinate means. We also distinguish the transformed Cholesky-coordinate mode from modes defined using covariance or precision coordinates. The model-selection procedure searches only over DAGs compatible with the specified ordering. Historical simulation and data examples illustrate the method; their evidentiary limitations and reproducibility requirements are stated explicitly.

math.ST↗
arXiv2011

Removing Gaussian Noise by Optimization of Weights in Non-Local Means

A new image denoising algorithm to deal with the additive Gaussian white noise model is given. Like the non-local means method, the filter is based on the weighted average of the observations in a neighborhood, with weights depending on the similarity of local patches. But in contrast to the non-local means filter, instead of using a fixed Gaussian kernel, we propose to choose the weights by minimizing a tight upper bound of mean square error. This approach makes it possible to define the weights adapted to the function at hand, mimicking the weights of the oracle filter. Under some regularity conditions on the target image, we show that the obtained estimator converges at the usual optimal rate. The proposed algorithm is parameter free in the sense that it automatically calculates the bandwidth of the smoothing kernel; it is fast and its implementation is straightforward. The performance of the new filter is illustrated by numerical simulations.

stat.OT↗
arXiv2011

Technical Report: Energy Evaluation of preamble Sampling MAC Protocols for Wireless Sensor Networks

The paper presents a simple probabilistic analysis of the energy consumption in preamble sampling MAC protocols. We validate the analytical results with simulations. We compare the classical MAC protocols (B-MAC and X-MAC) with LAMAC, a method proposed in a companion paper. Our analysis highlights the energy savings achievable with LA-MAC with respect to B-MAC and X-MAC. It also shows that LA-MAC provides the best performance in the considered case of high density networks under traffic congestion.

stat.OT↗
arXiv2011

A Statistical Significance Simulation Study for the General Scientist

When a scientist performs an experiment they normally acquire a set of measurements and are expected to demonstrate that their results are "statistically significant" thus confirming whatever hypothesis they are testing. The main method for establishing statistical significance involves demonstrating that there is a low probability that the observed experimental results were the product of random chance. This is typically defined as p < 0.05, which indicates there is less than a 5% chance that the observed results occurred randomly. This research study visually demonstrates that the commonly used definition for "statistical significance" can erroneously imply a significant finding. This is demonstrated by generating random Gaussian noise data and analyzing that data using statistical testing based on the established two-sample t-test. This study demonstrates that insignificant yet "statistically significant" findings are possible at moderately large sample sizes which are very common in many fields of modern science.

stat.OT↗
arXiv2011

Modern Portfolio Theory using SAS\textregistered OR

Investment approaches in financial instruments have been varied and often produce unpredictable results. Many investors in the earlier days of investment banking suffered catastrophical losses due to poor strategy and lack of understanding of the financial market. With the development of investment banking, many innovative investment strategies have been proposed to make portfolio returns higher than the overall market. One of the most famous theories of portfolio creation and management is the modern portfolio theory proposed by Harry Markowitz. In this paper, we shall apply the theory in creating a portfolio of stocks as well as managing it.

stat.OT↗
arXiv2011

Contending Parties: A Logistic Choice Analysis of Inter- and Intra-group Blog Citation Dynamics in the 2004 US Presidential Election

The 2004 US Presidential Election cycle marked the debut of Internet-based media such as blogs and social networking websites as institutionally recognized features of the American political landscape. Using a longitudinal sample of all DNC/RNC-designated blog-citation networks we are able to test the influence of various strategic, institutional, and balance-theoretic mechanisms and exogenous factors such as seasonality and political events on the propensity of blogs to cite one another over time. Capitalizing on the temporal resolution of our data, we utilize an autoregressive network regression framework to carry out inference for a logistic choice process. Using a combination of deviance-based model selection criteria and simulation-based model adequacy tests, we identify the combination of processes that best characterizes the choice behavior of the contending blogs.

cs.SI↗
arXiv2011

Markov Equivalences for Subclasses of Loopless Mixed Graphs

In this paper we discuss four problems regarding Markov equivalences for subclasses of loopless mixed graphs. We classify these four problems as finding conditions for internal Markov equivalence, which is Markov equivalence within a subclass, for external Markov equivalence, which is Markov equivalence between subclasses, for representational Markov equivalence, which is the possibility of a graph from a subclass being Markov equivalent to a graph from another subclass, and finding algorithms to generate a graph from a certain subclass that is Markov equivalent to a given graph. We particularly focus on the class of maximal ancestral graphs and its subclasses, namely regression graphs, bidirected graphs, undirected graphs, and directed acyclic graphs, and present novel results for representational Markov equivalence and algorithms.

stat.OT↗