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Journal articles on the topic 'Conditional assumptions'

Author: Grafiati

Published: 4 June 2021

Last updated: 5 February 2022

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1

SZTENCEL, MAGDALENA, and LEESA CLARKE. "Deontic commitments in conditional promises and threats: towards an exemplar semantics for conditionals." Language and Cognition 10, no. 3 (2018): 435–66. http://dx.doi.org/10.1017/langcog.2018.10.

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abstractThis paper studies two types of cognitive factors which have been assumed to underpin people’s interpretation of conditional promises and threats: logic and socio-cognitive assumptions about what conditional promisors and threateners are obliged and permitted to do. We consider whether the logic of conditionals is compatible with the socio-cognitive assumptions underlying their interpretation or whether the two come apart. From the classical logical accounts of conditionals, almost all modern theories have inherited a constraint which specifies that a conditional cannot be true if its

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Weidenfeld, Andrea, Klaus Oberauer, and Robin Hörnig. "Causal and noncausal conditionals: An integrated model of interpretation and reasoning." Quarterly Journal of Experimental Psychology Section A 58, no. 8 (2005): 1479–513. http://dx.doi.org/10.1080/02724980443000719.

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We present an integrated model for the understanding of and the reasoning from conditional statements. Central assumptions from several approaches are integrated into a causal path model. According to the model, the cognitive availability of exceptions to a conditional reduces the subjective conditional probability of the consequent, given the antecedent. This conditional probability determines people's degree of belief in the conditional, which in turn affects their willingness to accept logically valid inferences. In addition to this indirect pathway, the model contains a direct pathway: Ava

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Egger, H., and B. Hofmann. "Tikhonov regularization in Hilbert scales under conditional stability assumptions." Inverse Problems 34, no. 11 (2018): 115015. http://dx.doi.org/10.1088/1361-6420/aadef4.

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Glynn, Adam N., and Kevin M. Quinn. "Why Process Matters for Causal Inference." Political Analysis 19, no. 3 (2011): 273–86. http://dx.doi.org/10.1093/pan/mpr021.

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Our goal in this paper is to provide a formal explanation for how within-unit causal process information (i.e., data on posttreatment variables and partial information on posttreatment counterfactuals) can help to inform causal inferences relating to total effects—the overall effect of an explanatory variable on an outcome variable. The basic idea is that, in many applications, researchers may be able to make more plausible causal assumptions conditional on the value of a posttreatment variable than they would be able to do unconditionally. As data become available on a posttreatment variable,

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Andresel, Medina, Magdalena Ortiz, and Mantas Simkus. "Query Rewriting for Ontology-Mediated Conditional Answers." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 03 (2020): 2734–41. http://dx.doi.org/10.1609/aaai.v34i03.5660.

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Among many solutions for extracting useful answers from incomplete data, ontology-mediated queries (OMQs) use domain knowledge to infer missing facts. We propose an extension of OMQs that allows us to make certain assumptions—for example, about parts of the data that may be unavailable at query time, or costly to query—and retrieve conditional answers, that is, tuples that become certain query answers when the assumptions hold. We show that querying in this powerful formalism often has no higher worst-case complexity than in plain OMQs, and that these queries are first-order rewritable for DL-

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Champollion, Lucas, Ivano Ciardelli, and Linmin Zhang. "Breaking de Morgan's law in counterfactual antecedents." Semantics and Linguistic Theory 26 (October 15, 2016): 304. http://dx.doi.org/10.3765/salt.v26i0.3800.

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The main goal of this paper is to investigate the relation between the meaning of a sentence and its truth conditions. We report on a comprehension experiment on counterfactual conditionals, based on a context in which a light is controlled by two switches. Our main finding is that the truth-conditionally equivalent clauses (i) switch A or switch B is down and (ii) switch A and switch B are not both up make different semantic contributions when embedded in a conditional antecedent. Assuming compositionality, this means that (i) and (ii) differ in meaning, which implies that the meaning of a se

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HUANG, VIVIAN J., and DEJIAN LAI. "INTERIM ANALYSIS OF CLINICAL TRIALS: SIMULATION STUDIES OF CONDITIONAL POWER UNDER FRACTIONAL BROWNIAN MOTION." Fractals 27, no. 08 (2019): 1950133. http://dx.doi.org/10.1142/s0218348x19501330.

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Classical Brownian motion (BM) techniques for statistical monitoring of clinical trials have been widely used. The conditional power (CP) and [Formula: see text]-spending function-based boundary crossing probabilities are popular procedures for statistical hypothesis testing under the assumption of BM. However, in some clinical trials, the assumptions of BM may not be fully met for the design and data analysis. Therefore, a more general class of stochastic processes, fractional Brownian motion (FBM), was proposed in the literature to model the test statistics derived from interim analysis of c

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Kassberger, Stefan, and Thomas Liebmann. "An alternative axiomatic characterisation of pricing operators." Journal of Applied Probability 53, no. 4 (2016): 1257–64. http://dx.doi.org/10.1017/jpr.2016.78.

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Abstract In the spirit of the axiomatic approach by Rogers (1998) we show the equivalence between a set of assumptions on the behaviour of prices and the existence of a representation of these prices as conditional expectations. We rely on only weak assumptions and avoid any a priori modelling of negligible events or of any market filtration. Rather, both endogenously emerge along with the representation as conditional expectations.

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Stanghellini, Elena, and Marco Doretti. "On marginal and conditional parameters in logistic regression models." Biometrika 106, no. 3 (2019): 732–39. http://dx.doi.org/10.1093/biomet/asz019.

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Summary We derive the exact formula linking the parameters of marginal and conditional logistic regression models with binary mediators when no conditional independence assumptions can be made. The formula has the appealing property of being the sum of terms that vanish whenever parameters of the conditional models vanish, thereby recovering well-known results as particular cases. It also permits the disentangling of direct and indirect effects as well as quantifying the distortion induced by the omission of relevant covariates, opening the way to sensitivity analysis. As the parameters of the

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Pieper, Konstantin, and Daniel Walter. "Linear convergence of accelerated conditional gradient algorithms in spaces of measures." ESAIM: Control, Optimisation and Calculus of Variations 27 (2021): 38. http://dx.doi.org/10.1051/cocv/2021042.

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A class of generalized conditional gradient algorithms for the solution of optimization problem in spaces of Radon measures is presented. The method iteratively inserts additional Dirac-delta functions and optimizes the corresponding coefficients. Under general assumptions, a sub-linear [see formula in PDF] rate in the objective functional is obtained, which is sharp in most cases. To improve efficiency, one can fully resolve the finite-dimensional subproblems occurring in each iteration of the method. We provide an analysis for the resulting procedure: under a structural assumption on the opt

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Wooldridge, Jeffrey M. "Selection corrections for panel data models under conditional mean independence assumptions." Journal of Econometrics 68, no. 1 (1995): 115–32. http://dx.doi.org/10.1016/0304-4076(94)01645-g.

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12

Sanderson, Benjamin. "The role of prior assumptions in carbon budget calculations." Earth System Dynamics 11, no. 2 (2020): 563–77. http://dx.doi.org/10.5194/esd-11-563-2020.

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Abstract. Cumulative emissions budgets and net-zero emission target dates are often used to frame climate negotiations (Frame et al., 2014; Millar et al., 2016; Van Vuuren et al., 2016; Rogelj et al., 2015b; Matthews et al., 2012). However, their utility for near-term policy decisions is confounded by uncertainties in future negative emissions capacity (Fuss et al., 2014; Smith et al., 2016; Larkin et al., 2018; Anderson and Peters, 2016), in the role of non-CO2 forcers (MacDougall et al., 2015) and in the long-term Earth system response to forcing (Rugenstein et al., 2019; Knutti et al., 2017

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Rintanen, J. "Constructing Conditional Plans by a Theorem-Prover." Journal of Artificial Intelligence Research 10 (May 1, 1999): 323–52. http://dx.doi.org/10.1613/jair.591.

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The research on conditional planning rejects the assumptions that there is no uncertainty or incompleteness of knowledge with respect to the state and changes of the system the plans operate on. Without these assumptions the sequences of operations that achieve the goals depend on the initial state and the outcomes of nondeterministic changes in the system. This setting raises the questions of how to represent the plans and how to perform plan search. The answers are quite different from those in the simpler classical framework. In this paper, we approach conditional planning from a new viewpo

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Lu, Xiao. "Discrete Choice Data with Unobserved Heterogeneity: A Conditional Binary Quantile Model." Political Analysis 28, no. 2 (2019): 147–67. http://dx.doi.org/10.1017/pan.2019.29.

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In political science, data with heterogeneous units are used in many studies, such as those involving legislative proposals in different policy areas, electoral choices by different types of voters, and government formation in varying party systems. To disentangle decision-making mechanisms by units, traditional discrete choice models focus exclusively on the conditional mean and ignore the heterogeneous effects within a population. This paper proposes a conditional binary quantile model that goes beyond this limitation to analyze discrete response data with varying alternative-specific featur

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WRIGHT, THOMAS. "A CONDITIONAL DENSITY FOR CARMICHAEL NUMBERS." Bulletin of the Australian Mathematical Society 101, no. 3 (2020): 379–88. http://dx.doi.org/10.1017/s000497271900145x.

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Under sufficiently strong assumptions about the first prime in an arithmetic progression, we prove that the number of Carmichael numbers up to $X$ is $\gg X^{1-R}$, where $R=(2+o(1))\log \log \log \log X/\text{log}\log \log X$. This is close to Pomerance’s conjectured density of $X^{1-R}$ with $R=(1+o(1))\log \log \log X/\text{log}\log X$.

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Graham, Jinko, James Curran, and B. S. Weir. "Conditional Genotypic Probabilities for Microsatellite Loci." Genetics 155, no. 4 (2000): 1973–80. http://dx.doi.org/10.1093/genetics/155.4.1973.

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Abstract Modern forensic DNA profiles are constructed using microsatellites, short tandem repeats of 2–5 bases. In the absence of genetic data on a crime-specific subpopulation, one tool for evaluating profile evidence is the match probability. The match probability is the conditional probability that a random person would have the profile of interest given that the suspect has it and that these people are different members of the same subpopulation. One issue in evaluating the match probability is population differentiation, which can induce coancestry among subpopulation members. Forensic as

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Vatutin, Vladimir, and Elena Dyakonova. "Path to survival for the critical branching processes in a random environment." Journal of Applied Probability 54, no. 2 (2017): 588–602. http://dx.doi.org/10.1017/jpr.2017.19.

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Abstract A critical branching process {Zk, k = 0, 1, 2, ...} in a random environment is considered. A conditional functional limit theorem for the properly scaled process {log Zpu, 0 ≤ u < ∞} is established under the assumptions that Zn > 0 and p ≪ n. It is shown that the limiting process is a Lévy process conditioned to stay nonnegative. The proof of this result is based on a limit theorem describing the distribution of the initial part of the trajectories of a driftless random walk conditioned to stay nonnegative.

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18

Newton, Douglas P. "Found coins as indicators of coins in circulation: testing some assumptions." European Journal of Archaeology 9, no. 2-3 (2006): 211–27. http://dx.doi.org/10.1177/1461957107086124.

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Coin finds are used to inform discussion about coins in circulation and, hence, economic activity. This discussion often rests on the assumption that patterns in finds of accidentally lost coins mirror to a useful extent those of the coins in circulation at the time. Whenever possible, such assumptions should be tested. This study does this empirically with data from a known coinage. Conditional support was found for the assumption. There is also some evidence that coin size and denomination can affect the coin record but these variables did not add significantly to predictions about coins in

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Mukherjee, Kanchan. "M-ESTIMATION IN GARCH MODELS." Econometric Theory 24, no. 6 (2008): 1530–53. http://dx.doi.org/10.1017/s0266466608080602.

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This paper derives asymptotic normality of a class of M-estimators in the generalized autoregressive conditional heteroskedastic (GARCH) model. The class of estimators includes least absolute deviation and Huber's estimator in addition to the well-known quasi maximum likelihood estimator. For some estimators, the asymptotic normality results are obtained only under the existence of fractional unconditional moment assumption on the error distribution and some mild smoothness and moment assumptions on the score function.

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20

Sart, Mathieu. "Estimating the conditional density by histogram type estimators and model selection." ESAIM: Probability and Statistics 21 (2017): 34–55. http://dx.doi.org/10.1051/ps/2016026.

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We propose a new estimation procedure of the conditional density for independent and identically distributed data. Our procedure aims at using the data to select a function among arbitrary (at most countable) collections of candidates. By using a deterministic Hellinger distance as loss, we prove that the selected function satisfies a non-asymptotic oracle type inequality under minimal assumptions on the statistical setting. We derive an adaptive piecewise constant estimator on a random partition that achieves the expected rate of convergence over (possibly inhomogeneous and anisotropic) Besov

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Sterba, Sonya K. "Handling Missing Covariates in Conditional Mixture Models Under Missing at Random Assumptions." Multivariate Behavioral Research 49, no. 6 (2014): 614–32. http://dx.doi.org/10.1080/00273171.2014.950719.

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22

Xudong Luo and Chengqi Zhang. "Proof of the correctness of EMYCIN sequential propagation under conditional independence assumptions." IEEE Transactions on Knowledge and Data Engineering 11, no. 2 (1999): 355–59. http://dx.doi.org/10.1109/69.761668.

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23

Lechner, Michael, and Ruth Miquel. "Identification of the effects of dynamic treatments by sequential conditional independence assumptions." Empirical Economics 39, no. 1 (2009): 111–37. http://dx.doi.org/10.1007/s00181-009-0297-3.

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24

Artadi, Ari, and Hari Setiawan. "Penggunaan dan Fungsi Kalimat Kondisional Bahasa Jepang “to”, “tara”, “reba” dan “nara” Berdasarkan Modalitas dan Teori Teritori Informasi." JLA (Jurnal Lingua Applicata) 4, no. 1 (2020): 41. http://dx.doi.org/10.22146/jla.57300.

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In Japanese, four conjugate particles are usually used to form conditional sentence patterns, namely “to”, “tara”, “reba” and “nara”. Based on the use of their modality and information territory, they have different uses and functions. Data analysis of Japanese newspaper sentences using qualitative method showed that Japanese conditional sentences can be classified into two types. The first type is Repeated Factual Conditional Sentence that uses the conjugate particle “to”. This sentence is used when the speaker and listener are considered to know the contents of the information in it, thus ex

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MEN, ZHONGXIAN, TONY S. WIRJANTO, and ADAM W. KOLKIEWICZ. "A MULTISCALE STOCHASTIC CONDITIONAL DURATION MODEL." Annals of Financial Economics 11, no. 04 (2016): 1650020. http://dx.doi.org/10.1142/s2010495216500202.

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This paper studies a stochastic conditional duration model running on multiple time scales with the aim of better capturing the dynamics of a duration process of financial transaction data. New Markov chain Monte Carlo (MCMC) algorithms are developed for the model under three distributional assumptions about the innovation of the measurement equation for a two-component model. Simulation results suggest that the proposed model and MCMC method improve in-sample fits and duration forecasts. Most importantly applications to FIAT and IBM duration datasets indicate the existence of at least two fac

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Stern, Steven. "Approximate Solutions to Stochastic Dynamic Programs." Econometric Theory 13, no. 3 (1997): 392–405. http://dx.doi.org/10.1017/s0266466600005867.

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This paper examines the properties of various approximation methods for solving stochastic dynamic programs in structural estimation problems. The problem addressed is evaluating the expected value of the maximum of available choices. The paper shows that approximating this by the maximum of expected values frequently has poor properties. It also shows that choosing a convenient distributional assumptions for the errors and then solving exactly conditional on the distributional assumption leads to small approximation errors even if the distribution is misspecified.

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FRITZ, PETER, and JEREMY GOODMAN. "COUNTERFACTUALS AND PROPOSITIONAL CONTINGENTISM." Review of Symbolic Logic 10, no. 3 (2017): 509–29. http://dx.doi.org/10.1017/s1755020317000144.

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AbstractThis article explores the connection between two theses: the principle of conditional excluded middle for the counterfactual conditional, and the claim that it is a contingent matter which (coarse grained) propositions there are. Both theses enjoy wide support, and have been defended at length by Robert Stalnaker. We will argue that, given plausible background assumptions, these two principles are incompatible, provided that conditional excluded middle is understood in a certain modalized way. We then show that some (although not all) arguments for conditional excluded middle can in fa

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Ciardelli, Ivano. "Lifting conditionals to inquisitive semantics." Semantics and Linguistic Theory 26 (October 18, 2016): 732. http://dx.doi.org/10.3765/salt.v26i0.3811.

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This paper describes how any theory which assigns propositions to conditional sentences can be lifted to the setting of inquisitive semantics, where antecedents and consequents may be associated with multiple propositions. We show that the lifted account improves on the original account in two ways: first, it leads to a better analysis of disjunctive antecedents, which are treated as introducing multiple assumptions; second, it extends the original account to cover two further classes of conditional constructions, namely, unconditionals and conditional questions.

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Gitelman, Alix I. "Estimating Causal Effects From Multilevel Group-Allocation Data." Journal of Educational and Behavioral Statistics 30, no. 4 (2005): 397–412. http://dx.doi.org/10.3102/10769986030004397.

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In group-allocation studies for comparing behavioral, social, or educational interventions, subjects in the same group necessarily receive the same treatment, whereby a group and/or group-dynamic effect can confound the treatment effect. General counterfactual outcomes that depend on group characteristics, group membership, and treatment are developed to provide a structure for specifying causal effects of treatment in the multilevel setting. An average causal effect of treatment cannot be specified, however, without a simplifying assumption of group-membership invariance (i.e., no group-dynam

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Ahmad, Aboubacrène Ag, El Hadji Deme, Aliou Diop, and Stéphane Girard. "Estimation of the tail-index in a conditional location-scale family of heavy-tailed distributions." Dependence Modeling 7, no. 1 (2019): 394–417. http://dx.doi.org/10.1515/demo-2019-0021.

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AbstractWe introduce a location-scale model for conditional heavy-tailed distributions when the covariate is deterministic. First, nonparametric estimators of the location and scale functions are introduced. Second, an estimator of the conditional extreme-value index is derived. The asymptotic properties of the estimators are established under mild assumptions and their finite sample properties are illustrated both on simulated and real data.

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Mavroudeas, Stavros, and Costas Syriopoulos. "Testing Convergence And Divergence: The Data From Greece." Journal of Applied Business Research (JABR) 14, no. 1 (2011): 149. http://dx.doi.org/10.19030/jabr.v14i1.5735.

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<span>The convergence hypothesis is a popular tenet in modern discussions in macroeconomics and regional economics. It derives from the very fundamental properties of the neoclassical single-sector growth model; and its assumption of diminishing returns to scale. Following this theoretical framework a number of empirical tests (or unconditional or conditional -convergence) has been developed. This paper tests unconditional and conditional -convergence for the Greek economy. Three issues are being considered: (i) if there is regional convergence, (ii) if there is a North-Southern divide,

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Barker, Richard. "Theory and application of mark - recapture and related techniques to aerial surveys of wildlife." Wildlife Research 35, no. 4 (2008): 268. http://dx.doi.org/10.1071/wr07086.

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The key difficulty in assessing animal numbers from the air is that not all animals are seen by the observers. Methods for estimating detection probabilities, or accounting for imperfect detection, are reviewed including double surveys, use of sightability models, mark–resight, and mark–recapture. The assumptions needed for each method are considered as well as issues concerning survey design. For closed-population mark–recapture modelling particular attention is given to multiple observer studies. An emphasis is that an assumption of complete independence in double-observer studies is rarely

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Godden, David, and Frank Zenker. "Denying Antecedents and Affirming Consequents: The State of the Art." Informal Logic 35, no. 1 (2015): 88. http://dx.doi.org/10.22329/il.v35i1.4173.

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Recent work on conditional reasoning argues that denying the antecedent [DA] and affirming the consequent [AC] are defeasible but cogent patterns of argument, either because they are effective, rational, albeit heuristic applications of Bayesian probability, or because they are licensed by the principle of total evidence. Against this, we show that on any prevailing interpretation of indicative conditionals, the premises of DA and AC arguments do not license their conclusions without additional assumptions. The cogency of DA and AC inferences rather depends on contingent factors extrinsic to,

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Lambert, M. F., J. P. Whiting, and A. V. Metcalfe. "A non-parametric hidden Markov model for climate state identification." Hydrology and Earth System Sciences 7, no. 5 (2003): 652–67. http://dx.doi.org/10.5194/hess-7-652-2003.

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Abstract. Hidden Markov models (HMMs) can allow for the varying wet and dry cycles in the climate without the need to simulate supplementary climate variables. The fitting of a parametric HMM relies upon assumptions for the state conditional distributions. It is shown that inappropriate assumptions about state conditional distributions can lead to biased estimates of state transition probabilities. An alternative non-parametric model with a hidden state structure that overcomes this problem is described. It is shown that a two-state non-parametric model produces accurate estimates of both tran

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NIU, SI-LI, та HAN-YING LIANG. "NONLINEAR WAVELET ESTIMATION OF CONDITIONAL DENSITY UNDER LEFT-TRUNCATED AND α-MIXING ASSUMPTIONS". International Journal of Wavelets, Multiresolution and Information Processing 09, № 06 (2011): 989–1023. http://dx.doi.org/10.1142/s0219691311004419.

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In this paper, we construct a nonlinear wavelet estimator of conditional density function for a left truncation model. We provide an asymptotic expression for the mean integrated squared error (MISE) of the estimator. It is assumed that the lifetime observations form a stationary α-mixing sequence. Unlike for kernel estimator, the MISE expression of the nonlinear wavelet estimator is not affected by the presence of discontinuities in the curves.

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Brennan, Robert L., and Won-Chan Lee. "Conditional Scale-Score Standard Errors of Measurement under Binomial and Compound Binomial Assumptions." Educational and Psychological Measurement 59, no. 1 (1999): 5–24. http://dx.doi.org/10.1177/0013164499591001.

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Brennan, R. L., and W.-C. Lee. "Conditional Scale-Score Standard Errors of Measurement Under Binomial and Compound Binomial Assumptions." Educational and Psychological Measurement 59, no. 1 (1999): 5–24. http://dx.doi.org/10.1177/00131649921969703.

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Feng, Yunlong. "New Insights Into Learning With Correntropy-Based Regression." Neural Computation 33, no. 1 (2021): 157–73. http://dx.doi.org/10.1162/neco_a_01334.

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Stemming from information-theoretic learning, the correntropy criterion and its applications to machine learning tasks have been extensively studied and explored. Its application to regression problems leads to the robustness-enhanced regression paradigm: correntropy-based regression. Having drawn a great variety of successful real-world applications, its theoretical properties have also been investigated recently in a series of studies from a statistical learning viewpoint. The resulting big picture is that correntropy-based regression regresses toward the conditional mode function or the con

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Bartlett, Jonathan W., James R. Carpenter, Kate Tilling, and Stijn Vansteelandt. "Improving upon the efficiency of complete case analysis when covariates are MNAR." Biostatistics 15, no. 4 (2014): 719–30. http://dx.doi.org/10.1093/biostatistics/kxu023.

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Abstract Missing values in covariates of regression models are a pervasive problem in empirical research. Popular approaches for analyzing partially observed datasets include complete case analysis (CCA), multiple imputation (MI), and inverse probability weighting (IPW). In the case of missing covariate values, these methods (as typically implemented) are valid under different missingness assumptions. In particular, CCA is valid under missing not at random (MNAR) mechanisms in which missingness in a covariate depends on the value of that covariate, but is conditionally independent of outcome.

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Draxler, Clemens, and Stephan Dahm. "Conditional or Pseudo Exact Tests with an Application in the Context of Modeling Response Times." Psych 2, no. 4 (2020): 198–208. http://dx.doi.org/10.3390/psych2040017.

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This paper treats a so called pseudo exact or conditional approach of testing assumptions of a psychometric model known as the Rasch model. Draxler and Zessin derived the power function of such tests. They provide an alternative to asymptotic or large sample theory, i.e., chi square tests, since they are also valid in small sample scenarios. This paper suggests an extension and applies it in a research context of investigating the effects of response times. In particular, the interest lies in the examination of the influence of response times on the unidimensionality assumption of the model. A

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SCHERVISH, MARK J., TEDDY SEIDENFELD та JOSEPH B. KADANE. "NONCONGLOMERABILITY FOR COUNTABLY ADDITIVE MEASURES THAT ARE NOT κ-ADDITIVE". Review of Symbolic Logic 10, № 2 (2016): 284–300. http://dx.doi.org/10.1017/s1755020316000344.

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AbstractLet κ be an uncountable cardinal. Using the theory of conditional probability associated with de Finetti (1974) and Dubins (1975), subject to several structural assumptions for creating sufficiently many measurable sets, and assuming that κ is not a weakly inaccessible cardinal, we show that each probability that is not κ-additive has conditional probabilities that fail to be conglomerable in a partition of cardinality no greater than κ. This generalizes a result of Schervish, Seidenfeld, & Kadane (1984), which established that each finite but not countably additive probability has

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Douglas, Jeff, Hae Rim Kim, Brian Habing, and Furong Gao. "Investigating Local Dependence With Conditional Covariance Functions." Journal of Educational and Behavioral Statistics 23, no. 2 (1998): 129–51. http://dx.doi.org/10.3102/10769986023002129.

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The local dependence of item pairs is investigated via a conditional covariance function estimation procedure. The conditioning variable used in the procedure is obtained by a monotonic transformation of total score on the remaining items. Intuitively, the conditioning variable corresponds to the unidimensional latent ability that is best measured by the test. The conditional covariance functions are estimated using kernel smoothing, and a standardization to adjust for the confounding effect of item difficulty is introduced. The particular standardization chosen is an adaptation of Yule’s coef

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Jewsbury, Paul A. "Diagnostic Test Score Validation With a Fallible Criterion." Applied Psychological Measurement 43, no. 8 (2018): 579–96. http://dx.doi.org/10.1177/0146621618817785.

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Criterion-related validation of diagnostic test scores for a construct of interest is complicated by the unavailability of the construct directly. The standard method, Known Group Validation, assumes an infallible reference test in place of the construct, but infallible reference tests are rare. In contrast, Mixed Group Validation allows for a fallible reference test, but has been found to make strong assumptions not appropriate for the majority of diagnostic test validation studies. The Neighborhood model is adapted for the purpose of diagnostic test validation, which makes alternate, but als

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Siddiqi, Muhammad Hameed, Madallah Alruwaili, Amjad Ali, Saad Alanazi, and Furkh Zeshan. "Human Activity Recognition Using Gaussian Mixture Hidden Conditional Random Fields." Computational Intelligence and Neuroscience 2019 (August 18, 2019): 1–14. http://dx.doi.org/10.1155/2019/8590560.

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In healthcare, the analysis of patients’ activities is one of the important factors that offer adequate information to provide better services for managing their illnesses well. Most of the human activity recognition (HAR) systems are completely reliant on recognition module/stage. The inspiration behind the recognition stage is the lack of enhancement in the learning method. In this study, we have proposed the usage of the hidden conditional random fields (HCRFs) for the human activity recognition problem. Moreover, we contend that the existing HCRF model is inadequate by independence assumpt

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Bratton, Daniel J., Hywel C. Williams, Brennan C. Kahan, Patrick PJ Phillips, and Andrew J. Nunn. "When inferiority meets non-inferiority: Implications for interim analyses." Clinical Trials 9, no. 5 (2012): 605–9. http://dx.doi.org/10.1177/1740774512453220.

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Background The objective of a non-inferiority trial is to determine whether a new or existing treatment is not less effective than another existing or current treatment by more than a pre-specified margin, Δ, usually with the requirement that the new treatment has some other advantage such as reduced cost or lower toxicity. A possible but unusual result in a non-inferiority trial is for the confidence interval for the treatment effect to lie between zero and Δ, implying that the new treatment is both inferior and non-inferior to the control. Such a result could occur in non-inferiority trials

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Lavda, Frantzeska, Magda Gregorová, and Alexandros Kalousis. "Data-Dependent Conditional Priors for Unsupervised Learning of Multimodal Data." Entropy 22, no. 8 (2020): 888. http://dx.doi.org/10.3390/e22080888.

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One of the major shortcomings of variational autoencoders is the inability to produce generations from the individual modalities of data originating from mixture distributions. This is primarily due to the use of a simple isotropic Gaussian as the prior for the latent code in the ancestral sampling procedure for data generations. In this paper, we propose a novel formulation of variational autoencoders, conditional prior VAE (CP-VAE), with a two-level generative process for the observed data where continuous z and a discrete c variables are introduced in addition to the observed variables x. B

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Hess, Stephane. "Conditional parameter estimates from Mixed Logit models: distributional assumptions and a free software tool." Journal of Choice Modelling 3, no. 2 (2010): 134–52. http://dx.doi.org/10.1016/s1755-5345(13)70039-3.

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Baker, H. Kent, Abdul Rahman, and Samir Saadi. "The day-of-the-week effect and conditional volatility: Sensitivity of error distributional assumptions." Review of Financial Economics 17, no. 4 (2008): 280–95. http://dx.doi.org/10.1016/j.rfe.2007.09.003.

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Liang, Han-Ying, Deli Li, and Tianxuan Miao. "Berry–Esseen type bound of conditional mode estimation under truncation and strong mixing assumptions." Communications in Statistics - Theory and Methods 45, no. 17 (2016): 5077–97. http://dx.doi.org/10.1080/03610926.2014.936561.

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Safer-Lichtenstein, Aaron, Gary LaFree, and Thomas Loughran. "Studying Terrorism Empirically: What We Know About What We Don’t Know." Journal of Contemporary Criminal Justice 33, no. 3 (2017): 273–91. http://dx.doi.org/10.1177/1043986217697873.

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Although the empirical and analytical study of terrorism has grown dramatically in the past decade and a half to incorporate more sophisticated statistical and econometric methods, data validity is still an open, first-order question. Specifically, methods for treating missing data often rely on strong, untestable, and often implicit assumptions about the nature of the missing values. We draw on Manski’s idea of no-assumption bounds to demonstrate the vulnerability of empirical results to different tactics for treating missing cases. Using a recently available open-source database on political

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