Objective Probability Research Articles

Visual SLAM in dynamic environments based on object detection

A great number of visual simultaneous localization and mapping (VSLAM) systems need to assume static features in the environment. However, moving objects can vastly impair the performance of a VSLAM system which relies on the static-world assumption. To cope with this challenging topic, a real-time and robust VSLAM system based on ORB-SLAM2 for dynamic environments was proposed. To reduce the influence of dynamic content, we incorporate the deep-learning-based object detection method in the visual odometry, then the dynamic object probability model is added to raise the efficiency of object detection deep neural network and enhance the real-time performance of our system. Experiment with both on the TUM and KITTI benchmark dataset, as well as in a real-world environment, the results clarify that our method can significantly reduce the tracking error or drift, enhance the robustness, accuracy and stability of the VSLAM system in dynamic scenes.

Keynes Had Already Answered Ramsey’s 1922 and 1926 Critiques Concerning Objective, Logical Probability Relations on Pages 35–36 of the A Treatise on Probability

Ramsey’s 1922 and 1926 critiques about Keynes’s logical ,objective probability relations overlooked Keynes’s already specified response that Keynes had incorporated on pp. 35-36 of chapter III of the A Treatise on Probability FIVE YEARS before Ramsey made his critique .This fact calls into question (a) whether Ramsey ever actually read the book he claimed to be reviewing and (b) whether those adhering to Ramsey’s “critique “ ever read the A Treatise on Probability either. It is bizarre that these same unsupportable claims are being rehashed again in C. Misak’s autobiography on Ramsey in 2020.

Why Is Clive Bell, an Artist With No Training in Logic, Mathematics, Statistics or Probability, Being Cited as an Expert on J M Keynes’s a Treatise on Probability?

Keynes had already answered Ramsey’s incoherent( bizarre?) criticism that “… the obvious one is that there really do not seem to be any such things as the probability relations he describes ...on page 36 of the A Treatise on Probability BEFORE Ramsey ever made his criticism. Keynes pointed out that the “…analogy between orders of similarity and probability is so great that its apprehension will greatly assist that of the ideas I wish to convey.” Ramsey completely failed to grasp the analogy between similarity and probability before criticizing Keynes. No where does Ramsey show that he understands the analogy between probability and similarity that Keynes is using. Nor has any philosopher, economist, psychologist, sociologist, historian or decision theorist demonstrated any understanding of Keynes’s argument in the 20th or 21st century. Only in the writings of cognitive psychologists and cognitive scientists is their evidence that Keynes’s position has been understood. I know of NO such specialist who has critiqued Keynes’s position. This means that Ramsey’s critique is based on ignorance on his part. Before one can rationally criticize any argument of any type, the person doing the critique MUST demonstrate that he understands the position he is critiquing. Keynes’s introductory comments on p.36 were then explored in Part III of the A Treatise on Probability in far, far, far greater depth and detail by Keynes. Keynes’s objective probability relations are simply objective similarity relations existing between old known situations and new unknown situations. Human pattern recognition skills involve using resemblance functions based on past memory that projects past knowledge of old situations into new situations, where there are similarities that are seen to exist between the old, known situation and a new, unexplored situation by SOME researchers. One then can come up with a rational degree of belief regarding how some new situation will play out, given the similarities between the old and new situations. Herbert Simon independently rediscovered some parts of Keynes’s Part III analysis in the A Treatise on Probability that dealt with the connection between intuition and induction when he started to analyze the decision making capabilities of tournament chess players in Over the Board competition, where the players must make decisions under time constrain(a clock),in the 1950’s. Simon was a part of the developing fields of Cognitive Science and cognitive psychology that started in the 1950’s.Keynes ‘s positions on intuition, induction, similarity (dissimilarity), resemblances, analogy and pattern recognition are all accepted basic conclusions in these fields. Ramsey’s concept that supposed humans were capable of calculating exact, precise probabilities, using the purely mathematical laws of the probability calculus to make decisions, is completely rejected except as very special case. One very special case would be correspondence (postal) chess where games can last for years. Another special case would be chess computers, like Deep Blue, that were allowed to bring their “book” knowledge of opening, middle, and end game positions (gigantic libraries containing all known variations of past played games) with them to the chess board. Garry Kasparov, the then World Chess champion, defeated Deep Blue 4-2 in 1996 and lost a rematch 2.5-3.5 in 1997. No cognitive scientist or cognitive psychologist would accept Ramsey’s claims about decision making by humans, be it in 1950 or 2020, because all of the empirical and experimental evidence is completely against Ramsey’s position on the ability of humans to use precise probability. It is very annoying to find in recent reviewers of Misak’s book, including Misak’s own commentary on Ramsey, a reliance on a completely and technically ignorant artist friend of Keynes, Clive Bell, who had no idea about what Keynes was doing in the A Treatise on Probability.The reason is simply because he was completely illiterate of any knowledge of mathematics statistics logic, and probability. I find it bizarre that he is considered a legitimate source that supposedly validates Ramsey’s silly, ignorant comments about Keynes’s “objective probability relations”. The argument seems to go like this ,where (a) ,(b) and (c) are the premises of the argument and (d) is the conclusion of the argument: (a) Ramsey was a great mathematical and logical genius (b) Clive Bell lived and talked with Keynes (c) Clive Bell stated that Ramsey’s critique demolished Keynes’s logical theory of probability (d) Ramsey’s critique demolished Keynes’s logical theory of probability This is what Misak’s argument amounts to.

Replication: Belief elicitation with quadratic and binarized scoring rules

Researchers increasingly elicit beliefs to understand the underlying motivations of decision makers. Two commonly used methods are the quadratic scoring rule (QSR) and the binarized scoring rule (BSR). Hossain and Okui (2013) use a within-subject design to evaluate the performance of these two methods in an environment where subjects report probabilistic beliefs over binary outcomes with objective probabilities. In a near replication of their study, we show that their results continue to hold with a between-subject design. This is an important validation of the BSR given that researchers typically implement only one method to elicit beliefs. In favor of the BSR, reported beliefs are less accurate under the QSR than the BSR. Consistent with theoretical predictions, risk-averse subjects distort their reported beliefs under the QSR.

Number of Near-Earth Objects and Formation of Lunar Craters over the Last Billion Years

We compare the number of lunar craters larger than 15 km across and younger than 1.1 Ga to the estimates of the number of craters that could have been formed for 1.1 Ga if the number of near-Earth objects and their orbital elements during that time were close to the corresponding current values. The comparison was performed for craters over the entire lunar surface and in the region of the Oceanus Procellarum and maria on the near side of the Moon. In these estimates, we used the values of collision probabilities of near-Earth objects with the Moon and the dependences of the crater diameters on the impactor sizes. According to the estimates made by different authors, the number density of known Copernican craters with diameters D>15 km in mare regions is at least double the corresponding number for the remaining lunar surface. Our estimates do not contradict the growth in the number of near-Earth objects after probable catastrophic fragmentations of large main-belt asteroids, which may have occurred over the recent 300 Ma; however, they do not prove this increase. Particularly, they do not conflict with the inference made by Mazrouei et al. (2019) that 290 Ma ago the frequency of collisions of near-Earth asteroids with the Moon increased by 2.6 times. For a probability of a collision of an Earth-crossing object (ECO) with the Earth in a year equaled to 10^-8, our estimates of the number of craters agree with the model, according to which the number densities of the 15-km Copernican craters for the whole lunar surface would have been the same as that for mare regions if the data by Losiak et al. (2015) for D<30 km were as complete as those for D>30 km. With this collision probability of ECOs with the Earth and for this model, the cratering rate may have been constant over the recent 1.1 Ga.

User Equilibrium Analysis Considering Travelers’ Context-Dependent Route Choice Behavior on the Risky Traffic Network

This paper studies travelers’ context-dependent route choice behavior in a risky trafficnetwork from a long-term perspective, focusing on the effect of travelers’ salience characteristics. In particular, a flow-dependent salience theory is proposed for this analysis, where the flow denotes the traffic flow on the risky route. In the proposed model, travelers’ attention is drawn to the salient travel utility, and the objective probabilities of the state of the world are replaced by the decision weights distorted in favor of this salient travel utility. A long-run user equilibrium will be achieved when no traveler can improve his or her salient travel utility by unilaterally changing routes, termed salient user equilibrium, which extends the scope of the Wardropian user equilibrium. Furthermore, we prove the existence and uniqueness of this salient user equilibrium. Finally, numerical studies demonstrate our theoretical findings. The equilibrium results show non-intuitive insights into travelers’ route choice behavior. (1) Travelers can be risk-seeking (the travel utility of a risky route is small with a relatively high probability), risk-neutral (in special situations), or risk-averse (the travel utility of a risky route is large with a relatively high probability), which depends on the salient state. (2) The extent of travelers’ risk-seeking or risk-averse behavior depends on their extent of salience bias, while the risk-neutral behavior is irrelative to this salience bias.

Consistency in probability processing as a function of affective context and numeracy

AbstractProcessing information about probabilities is an integral part of decision making under risk. Even when objective probabilities are explicitly provided, people tend to distort them, which is reflected by an inverted S‐shaped probability weighting function. Such distortions depend on different factors such as numeracy and affect. The present study contributes to the understanding of how people use probabilities in risky decision making by introducing the concept of consistency in probability processing―a measure of how coherent people are in using objective probabilities. We hypothesized that consistency would depend on factors similar to those that influence the shape of the probability weighting function. Moreover, we predicted that probability processing consistency would be related to better decision outcomes in an experimental betting task. In three experiments, participants were presented with the probability of a potential gain/loss and had to place a bet on a given chance to maximize their total earnings. We defined probability processing consistency as the variance of bets placed on the same probability value, with higher variance indicating lower consistency. We found that consistency in probability processing was lower in relatively affect‐rich conditions and greater for people with higher numeracy. Additionally, people who exhibited more consistent processing of probabilities gained higher earnings from the experimental task irrespective of whether their betting strategy was optimal and of their risk preference. Our findings imply that consistency in processing probabilities may be an important factor in understanding betting strategies and the quality of decisions.

Hit Probability of Cylindrical Objects Dropped on Pipelines in Offshore Operations

AbstractIn offshore oil and gas developments, it is mandatory to have a dropped-objects plan that can be provided to the Bureau of Safety and Environmental Enforcement upon request. Dropped objects...

User decisions, and how these could guide developments in probabilistic forecasting

AbstractWe investigate how users combine objective probabilities with their own subjective feelings when deciding how to act on weather forecast information. Results are based on two scenarios investigated at a Live Science event held by the Royal Meteorological Society. When deciding whether to go to the beach with the possibility of warm, dry weather, we find that users attempt to identify their ‘Bayes Action’: the one which minimises their expected negative feeling or utility. Key factors are the ‘thrill’ of a nice day at the beach and the ‘pain’ of coping with, for example, children in wet weather, and the costs of travel. The users' threshold probabilities for deciding to go to the beach thus approximately define their distribution of cost/loss ratios. This is used to calculate a ‘User Brier Score’ (UBS): a measure of the overall utility to society, and which could be used to guide forecast system development. When applied to operational ensemble forecasts issued by the European Centre for Medium‐Range Weather Forecasts (ECMWF) over the period 1995–2018, the UBS tends to be higher (i.e., worse) than the Brier Score, largely because users tended not to exhibit high cost/loss ratios. When deciding whether to leave a campsite in the face of potentially dangerous gales, users try to find a balance between the ‘regret’ of serious injury and the ‘pain’ of spoiling an enjoyable holiday. Some users decide to stay even at high probabilities of serious consequences – partly due to a lack of experience. On the other hand, forecasts suffer from ‘complete misses’ – where probabilities of zero are accompanied by non‐negligible outcome frequencies. These dominate the overall Brier Score. The frequency of complete misses halved over the period 1995–2018: a welcome improvement for users who do wish to avoid danger at low probabilities.

Impact on collision probability by post mission disposal and active debris removal

The collision probabilities of debris objects with and without Post Mission Disposal (PMD) and Active Debris Removal (ADR) are evaluated and discussed. A debris evolutionary model named NEODEEM was jointly developed by Kyushu University and JAXA for use in predicting future debris populations and calculating collision probabilities. The collision probability in each altitude bin is initially compared with and without PMD or ADR. Then a case involving a large satellite constellation is also discussed. The effective number of debris objects at each altitude for the PMD success rates of the large constellation and the collision probability at each altitude are calculated. The collision probability per unit time will increase when a small satellite utilizes a drag augmentation sail or a tether as a PMD device, but the dwell time will be greatly reduced. A collision with a sail or tether will be non-catastrophic collision. Therefore, the use of such devices will reduce the cumulative collision probability and expected number of debris fragments.

Life insurance and life settlement markets with overconfident policyholders

We analyze how the life settlement market—the secondary market for life insurance—may affect consumer welfare in a dynamic equilibrium model of life insurance with one-sided commitment and overconfident policyholders. In our model, policyholders may lapse their life insurance policies when they lose their bequest motives; however, they are overconfident in the sense that they may underestimate the probability of losing their bequest motives. We show that in the competitive equilibrium without life settlement, overconfident consumers will buy life insurance contracts with “too much” reclassification risk insurance for later periods. The life settlement market can impose a limit on the extent to which primary insurers can exploit overconfident consumers. We show that the life settlement market may increase the equilibrium consumer welfare of overconfident consumers when they are sufficiently “vulnerable” in the sense that they have a sufficiently large intertemporal elasticity of substitution of consumption. Our result is robust to alternative specifications where (i) insurers cannot observe the subjective or objective probability that policyholders will lose their bequest motives; (ii) insurers can include health-contingent cash surrender values (CSVs) in the life insurance contract; and (iii) policyholders underestimate their future mortality risk.

Probabilistic kingdom: problem of objectivity in contemporary science

In modern science, the theory of probability is one of the basic tools. Scientists using probability often refer to its objective interpretation. They emphasize that their probabilistic hypotheses concern objective facts, not degrees of belief. Accordingly, the following questions arise: What is the meaning of this type of probabilistic hypothesis? Is the assumption of objectivity necessary? The paper addresses these questions by analyzing objective probability in the context of the scientific debate on determinism. Two types of arguments will be presented. On the one hand, there is the assertion that objective probability can exist only in an indeterministic world. Then, on the other hand — I analyze the assertions of those who believe in the co‑existence of objective probability and determinism. As a result I show that the acceptance of deterministic and indeterministic fields as possible areas where objective probability can occur is extremely problematic. Depending on the chosen area we encounter different types of problems. Therefore, I show that a significant number of these problems are associated with the acceptance of incorrect metaphysical assumptions. And finally, I postulate that the objectivity of probability (and assumptions pertaining to it) can be reduced (without any losses) to the epistemic variant.

George Box’s Realization, That All Models, Especially Statistical Models, Are Wrong Means That It Is Impossible for There to Be Any True Probabilities, True Models, True Theories, True Expectations or True (Accepted) Hypotheses: The Claims, Made By Rational Expectations Proponents About True Objective Probabilities, True Models, True Expectations, True Expected Values, etc., Have No Scientific Foundation

R. Muth’s 1961 paper in Econometrica is an example of an academic economist suffering from extreme and extraordinary ignorance about very basic scientific, statistical, methodological, epistemological, philosophical, and logical tenets. These tenets were all discussed rigorously by Haavelmo in his 1944 paper in Econometrica on methodological and epistemological issues related to the question about exactly what conclusions a statistical model using economic data could support as far as sound(never valid, right ,correct, true). Haavelmo’s entire 115 page article can be summarized briefly by George Box’s brief statement noted above .Muth’s belief ,that economists had derived true theories and true models is simple nonsense. What Muth should have argued in his 1961 article, but did not, is that rational expectations, when compared to its rivals,was a better model compared to the rival models in terms of minimizing its forecasting error.Of course, Muth would have had to have supported this claim of forecast superiority with explicit proper scoring rule studies showing that the rational expectations statistical model did in fact yield superior forecast results. No such study exists at the present time because no proponent of the rational expectations hypothesis has ever demonstrated such forecasting superiority. Two additional, very severe problems result from Muth’s confused understanding of what scientific modeling is capable of regarding the specification of objective and subjective probabilities or probability distributions. First,It is simply impossible to assume the truth of the objective theory of a limiting frequency interpretation of probability and then claim that decision makers can learn from experience what the convergence properties of such a distribution are in the short run when such properties will only manifest themselves in the far ,distant(infinite)long run. It is impossible for any human ,unless rational expectations proponents are claiming that there are actual decision makers who live to infinity,to learn of such properties .Kolmogorov made it quite clear that the strengthened limiting frequency interpretation he had provided for R.Von Mises law of large numbers,which resulted from the substitution of the assumption of countable additivity for finite additivity “ …does not contribute anything to substantiate the application of the results of probability theory to real practical problems where we always have to deal with a finite number of trials”(Kolmogorov). Second, given L. J. Savage’s clearly expressed and emphasized restrictions concerning the applicability of the theory of subjective probability and expected subjective utility to the short run at the micro level ,any attempt to apply Savage’s theory at the macro level or to the intermediate to long run or intertemporally over infinite time is “utterly preposterous” and complete”nonsense according to Savage.This means that Muth’s claim about subjective probability transforming itself into objective probability might only be considered a subject for possible study and scrutiny in the short run at the microeconomic level. Economists and econometricians are good number crunchers only. Their subjective claims and beliefs about infinitely lived decision makers, who are able to learn about so called true ,objective probability distributions ,are “utterly preposterous “ and anti scientific. William McChesney Martin ,FRS chair of the BOD in Washington,D.C.from 1950 and 1970 ,correctly kept the econometricians ,economists, and Paul Volcker in the basement of the NY Federal Reserve Bank, where they had no input or say in actual or proposed monetary policy decisions. Martin realized that the extremely narrow understanding of what was required in the real world of monetary policy on the part of economists necessitated this setup. Alan Greenspan, in his 2004 (May) paper in the AER ,also rejected the applicability of the theory of rational expectations in monetary policy from 1987 to 2005,given his emphasis on the importance of taking into consideration all models, including those dealing with uncertainty where the knowledge base ranged from complete ignorance to complete knowledge. On the other hand ,A. Burns, P.Volcker,B. Bernanke, and T .Geithner did believe that their mathematical and econometric models were true. One can compare the great success of Martin and Greenspan with the failures of Volcker and Bernanke(Geithner) and reach the conclusion that it is time to return the economists and econometricians back to the basement of the FRBNY where they belong as effective and useful number crunchers only.

Correlation of test results and influence of a mass balance constraint on risks in conformity assessment of a substance or material

Abstract When components of a substance or material are subject to a mass balance constraint, test results of the components’ contents are intrinsically correlated because of the constraint. This so-called ‘spurious’ correlation is observed in addition to possible metrologically-related correlation of test results, and natural and/or technological correlation of the components’ contents. Such correlations may influence understanding of test results and evaluation of risks of false decisions, due to measurement uncertainty, in conformity assessment of the substance or material. The objective of the present paper is the development of a technique for appropriate evaluation of the risks. A Bayesian multivariate approach to evaluate the conformance probability of materials or objects and relevant risks is discussed for different scenarios of the data modelling, taking into account all observed correlations. A Monte Carlo method, including the mass balance constraint, written in the R programming environment, is provided for the necessary calculations.

Klasifikasi Keatraktifan e-Commerce Indonesia Menggunakan Algoritma Regresi Logistik

The rapid development of the internet gives a significant influence in various aspects of life, data mining is the search for value-added processes one of a series of knowledge discovery in databases (KDD). Utilization of data mining can be seen from two aspects, namely commercial and scientific. The collection of test datasets is done by observing the research object on the analysis site that provides vital information and forecast data for the local e-commerce web. The study was conducted by exploration and experimentation, the standard research method used in testing is the cross industry standard process for data mining (CRISP-DM) which consists of 6 phases with the Weka framework 3-8-3. Logistic regression algorithm is a method of data analysis that formulates the response variable with one or more predictor variables. The results of testing the value of e-commerce attractiveness in the confusion matrix, 5 are categorized as having high probability of investment objectives and profiles, 1 are categorized as having good investment probability prospects, 2 are categorized as having good investment probabilities with promising profiles and 1 with promising investment probabilities and profiles not good and 31 in terms of probability and profile is not good. While the results for the Origin class confusion matrix are 31 identified from local Indonesia with confusion 5, 4 from Global with uncertainty 0

Entropy binomial tree method and calibration for the volatility smile

In this paper, we combine the maximum entropy principle with binomial tree to construct a non-recombining entropy binomial tree pricing model under the volatility that is a function of time, and give the rate of convergence. The model may yield an unbiased and objective probability. In addition, we research the calibration problem of volatility with the entropy binomial tree, and adopt an exterior penalty method to transform this problem into a nonlinear unconstrained optimization problem. For the optimization problem, we use the quasi-Newton algorithm. Finally, we test our model by numerical examples and options data on the S&P 500 index. The results confirm the effectiveness of the entropy binomial tree pricing model.

Stochastic representation decision theory: How probabilities and values are entangled dual characteristics in cognitive processes

Humans are notoriously bad at understanding probabilities, exhibiting a host of biases and distortions that are context dependent. This has serious consequences on how we assess risks and make decisions. Several theories have been developed to replace the normative rational expectation theory at the foundation of economics. These approaches essentially assume that (subjective) probabilities weight multiplicatively the utilities of the alternatives offered to the decision maker, although evidence suggest that probability weights and utilities are often not separable in the mind of the decision maker. In this context, we introduce a simple and efficient framework on how to describe the inherently probabilistic human decision-making process, based on a representation of the deliberation activity leading to a choice through stochastic processes, the simplest of which is a random walk. Our model leads naturally to the hypothesis that probabilities and utilities are entangled dual characteristics of the real human decision making process. It predicts the famous fourfold pattern of risk preferences. Through the analysis of choice probabilities, it is possible to identify two previously postulated features of prospect theory: the inverse S-shaped subjective probability as a function of the objective probability and risk-seeking behavior in the loss domain. It also predicts observed violations of stochastic dominance, while it does not when the dominance is evident. Extending the model to account for human finite deliberation time and the effect of time pressure on choice, it provides other sound predictions: inverse relation between choice probability and response time, preference reversal with time pressure, and an inverse double-S-shaped probability weighting function. Our theory, which offers many more predictions for future tests, has strong implications for psychology, economics and artificial intelligence.

Distributing Responsibility

Distributing Responsibility

Conditional Degree of Belief and Bayesian Inference

Why are conditional degrees of belief in an observation E, given a statistical hypothesis H, aligned with the objective probabilities expressed by H? After showing that standard replies (ratio analysis of conditional probability, chance-credence coordination) are not satisfactory, I develop a suppositional analysis of conditional degree of belief, transferring Ramsey’s classical proposal to statistical inference. The analysis saves the alignment, explains the role of chance-credence coordination, and rebuts the charge of arbitrary assessment of evidence in Bayesian inference. Finally, I explore the implications of this analysis for Bayesian reasoning with idealized models in science.

Predictive Evidence and Unpredictable Freedom

Abstract When determining in criminal proceedings whether an individual performed a certain culpable action, predictive evidence is often ignored. Most notably, and with few exceptions, base-rates are excluded. The hostility of criminal fact-finding towards predictive evidence is also apparent in the deeply rooted suspicion of bad character and previous convictions. In this paper, I seek to explain this hostility by suggesting that criminal fact-finding implicitly adheres to the view that culpable conduct requires free will that is necessarily unpredictable. While theorists tend to agree that it is possible to predict a free action, at least with some degree of confidence, I contend that criminal fact-finding adheres to the view that free actions cannot have either subjective or objective probabilities. It is not only the lack of sufficient information that prevents an accurate prediction of how an agent will act freely: free actions cannot be predicted because their probability does not exist.