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  • Regular conditional probability
  • Concept in probability theory

    In probability theory, regular conditional probability is a concept that formalizes the notion of conditioning on the outcome of a random variable. The

    Regular conditional probability

    Regular_conditional_probability

  • Conditional probability
  • Probability of an event occurring, given that another event has already occurred

    In probability theory, conditional probability is a measure of the probability of an event occurring, given that another event (by assumption, presumption

    Conditional probability

    Conditional probability

    Conditional_probability

  • Conditional probability distribution
  • Probability theory and statistics concept

    In probability theory and statistics, the conditional probability distribution is a probability distribution that describes the probability of an outcome

    Conditional probability distribution

    Conditional_probability_distribution

  • Conditional expectation
  • Expected value of a random variable given that certain conditions are known to occur

    In probability theory, the conditional expectation, conditional expected value, or conditional mean of a random variable is its expected value evaluated

    Conditional expectation

    Conditional_expectation

  • Conditional mutual information
  • Information theory

    In probability theory, particularly information theory, the conditional mutual information is, in its most basic form, the expected value of the mutual

    Conditional mutual information

    Conditional mutual information

    Conditional_mutual_information

  • Conditioning (probability)
  • Probability theory term

    is formalized in probability theory by conditioning. Conditional probabilities, conditional expectations, and conditional probability distributions are

    Conditioning (probability)

    Conditioning_(probability)

  • Ionescu-Tulcea theorem
  • Probability theorem

    particular, the theory of Markov chains. Disintegration theorem Regular conditional probability Klenke, Achim (2013). Wahrscheinlichkeitstheorie (3rd ed.)

    Ionescu-Tulcea theorem

    Ionescu-Tulcea_theorem

  • Bayes' theorem
  • Mathematical rule for inverting probabilities

    inverting conditional probabilities, allowing the probability of a cause to be found given its effect. For example, with Bayes' theorem, the probability that

    Bayes' theorem

    Bayes'_theorem

  • Regular
  • Topics referred to by the same term

    Partition regularity Regular cardinal, a cardinal number that is equal to its cofinality Regular modal logic Regular conditional probability, a concept that

    Regular

    Regular

  • List of probability topics
  • Conditional expectation Conditional probability distribution Regular conditional probability Disintegration theorem Bayes' theorem de Finetti's theorem

    List of probability topics

    List_of_probability_topics

  • Disintegration theorem
  • Theorem in measure theory

    the measure space in question. It is related to the existence of conditional probability measures. In a sense, "disintegration" is the opposite process

    Disintegration theorem

    Disintegration_theorem

  • Standard probability space
  • Type of probability space

    conditional probability measures (see Itô 1984, Sect. 3.5), disintegration of measure (see Kechris 1995, Exercise (17.35)), and regular conditional probabilities

    Standard probability space

    Standard_probability_space

  • Outline of probability
  • Overview of and topical guide to probability

    The axioms of probability Boole's inequality Probability interpretations Bayesian probability Frequency probability Conditional probability The law of total

    Outline of probability

    Outline_of_probability

  • Conditional variance
  • Variance of a random variable given value of other variables

    In probability theory and statistics, a conditional variance is the variance of a random variable given the value(s) of one or more other variables. Particularly

    Conditional variance

    Conditional_variance

  • Markov chain
  • Random process independent of past history

    mapping of these to states. The Markov property states that the conditional probability distribution for the system at the next step (and in fact at all

    Markov chain

    Markov chain

    Markov_chain

  • Category of Markov kernels
  • Category whose objects are measurable spaces and whose morphisms are Markov kernels

    {\displaystyle B\in {\mathcal {G}}} , which suggests an interpretation as conditional probability. The category Stoch has: As objects, measurable spaces; As morphisms

    Category of Markov kernels

    Category_of_Markov_kernels

  • Lifting theory
  • Notion in measure theory

    to occur Borel–Kolmogorov paradox – Conditional probability paradox Regular conditional probability von Neumann, John (1931). "Algebraische Repräsentanten

    Lifting theory

    Lifting_theory

  • Buffon's needle problem
  • Question in geometric probability

    2015. The problem formulation here avoids having to work with Regular conditional probability densities. Aigner, Martin; Ziegler, Günter M. (2013). Proofs

    Buffon's needle problem

    Buffon's needle problem

    Buffon's_needle_problem

  • Probability distribution of extreme points of a Wiener stochastic process
  • motion and fluctuations in financial markets. A formula for the conditional probability distribution of the extremum of the Wiener process and a sketch

    Probability distribution of extreme points of a Wiener stochastic process

    Probability_distribution_of_extreme_points_of_a_Wiener_stochastic_process

  • Space (mathematics)
  • Mathematical set with some added structure

    standard probability space a conditional expectation may be treated as the integral over the conditional measure (regular conditional probabilities, see also

    Space (mathematics)

    Space (mathematics)

    Space_(mathematics)

  • Hidden Markov model
  • Statistical Markov model

    called a trellis diagram) denote conditional dependencies. From the diagram, it is clear that the conditional probability distribution of the hidden variable

    Hidden Markov model

    Hidden_Markov_model

  • Catalog of articles in probability theory
  • (2:DC) Conditional random field / (F:R) Disintegration theorem / anl (2:G) Inverse probability / Bay Luce's choice axiom Regular conditional probability /

    Catalog of articles in probability theory

    Catalog_of_articles_in_probability_theory

  • Bayesian probability
  • Interpretation of probability

    Bayesian probability (/ˈbeɪziən/ BAY-zee-ən or /ˈbeɪʒən/ BAY-zhən) is an interpretation of the concept of probability, in which, instead of frequency or

    Bayesian probability

    Bayesian_probability

  • Perfect measure
  • ISBN 0-8218-3889-X. MR 2169627. Rodine, R. H. (1966). "Perfect probability measures and regular conditional probabilities". Ann. Math. Statist. 37: 1273–1278. Sazonov,

    Perfect measure

    Perfect_measure

  • Random walk
  • Process forming a path from many random steps

    that of a random walk on a regular lattice, where at each step the location jumps to another site according to some probability distribution. In a simple

    Random walk

    Random walk

    Random_walk

  • Vine copula
  • Graphical tool in probability

    high-dimensional probability distributions. A regular vine is a special case for which all constraints are two-dimensional or conditional two-dimensional. Regular vines

    Vine copula

    Vine_copula

  • Markov kernel
  • Concept in probability theory

    In probability theory, a Markov kernel (also known as a stochastic kernel or probability kernel) is a map that in the general theory of Markov processes

    Markov kernel

    Markov_kernel

  • Spanish verbs
  • Verbs in the Spanish language

    construction—unlike the future simple form—is not used in the "probability" sense to express conjecture. The conditional mood describes potential events without reference

    Spanish verbs

    Spanish verbs

    Spanish_verbs

  • Bayesian epistemology
  • Probabilistic theory of knowledge

    evidence. The axioms of probability and the principal principle belong to the static principles while the principle of conditionalization governs the dynamic

    Bayesian epistemology

    Bayesian_epistemology

  • List of statistics articles
  • expectation Conditional independence Conditional probability Conditional probability distribution Conditional random field Conditional variance Conditionality principle

    List of statistics articles

    List_of_statistics_articles

  • Frequentist probability
  • Interpretation of probability

    Frequentist probability or frequentism is an interpretation of probability; it defines an event's probability (the long-run probability) as the limit

    Frequentist probability

    Frequentist probability

    Frequentist_probability

  • Random graph
  • Graph generated by a random process

    {p} \in R^{m}} , conditional random graphs are models in which the probability measure P {\displaystyle P} assigns zero probability to all graphs such

    Random graph

    Random graph

    Random_graph

  • Homoscedasticity and heteroscedasticity
  • Statistical property

    heteroscedasticity, which led to his formulation of the autoregressive conditional heteroscedasticity (ARCH) modeling technique. Consider the linear regression

    Homoscedasticity and heteroscedasticity

    Homoscedasticity and heteroscedasticity

    Homoscedasticity_and_heteroscedasticity

  • Softmax function
  • Smooth approximation of one-hot arg max

    normalized exponential function, converts a tuple of K real numbers into a probability distribution over K possible outcomes. It is a generalization of the

    Softmax function

    Softmax_function

  • Binomial regression
  • Regression analysis technique

    be binomially distributed conditional on the explanatory variables X. The number of trials n is known, and the probability of success for each trial p

    Binomial regression

    Binomial_regression

  • Metropolis–Hastings algorithm
  • Monte Carlo algorithm

    {\displaystyle P(\theta )} the prior probability density and Q {\displaystyle Q} the (conditional) proposal probability. Genetic algorithms Mean-field particle

    Metropolis–Hastings algorithm

    Metropolis–Hastings algorithm

    Metropolis–Hastings_algorithm

  • Sampling (statistics)
  • Selection of data points in statistics

    the sample design, particularly in stratified sampling. Results from probability theory and statistical theory are employed to guide the practice. In

    Sampling (statistics)

    Sampling (statistics)

    Sampling_(statistics)

  • Venn diagram
  • Diagram that shows all possible logical relations between a collection of sets

    elementary set theory, and to illustrate simple set relationships in probability, logic, statistics, linguistics and computer science. A Venn diagram

    Venn diagram

    Venn diagram

    Venn_diagram

  • Classical conditioning
  • Aspect of learning procedure

    ugly, failure). These words were systematically paired with the two conditional stimuli nationalities such that one always appeared with positive words

    Classical conditioning

    Classical_conditioning

  • Failure rate
  • Frequency with which an engineered system or component fails

    can be interpreted as the instantaneous failure rate under the conditional probability that the system or component has already survived to time t {\displaystyle

    Failure rate

    Failure_rate

  • Continuous-time Markov chain
  • Probability concept

    sij, and represents the conditional probability of transitioning from state i into state j. These conditional probabilities may be found by s i j = {

    Continuous-time Markov chain

    Continuous-time_Markov_chain

  • Probabilistic context-free grammar
  • Grammar model in linguistics

    extend regular grammars. Each production is assigned a probability. The probability of a derivation (parse) is the product of the probabilities of the

    Probabilistic context-free grammar

    Probabilistic_context-free_grammar

  • Prospect theory
  • Theory of behavioral economics

    wealth, as well as a probability-weighting function that reflects the tendency of individuals to overweight small probabilities and underweight large

    Prospect theory

    Prospect theory

    Prospect_theory

  • Lester Dubins
  • American mathematician

    "On Existence and Non-Existence of Proper, Regular, Conditional Distributions". The Annals of Probability. 3 (5): 741–752. doi:10.1214/aop/1176996261

    Lester Dubins

    Lester Dubins

    Lester_Dubins

  • Turing completeness
  • Ability of a computing system to simulate Turing machines

    and multipliers were built and improved, but they could not perform a conditional branch and therefore were not Turing-complete. In the late 19th century

    Turing completeness

    Turing completeness

    Turing_completeness

  • Realis mood
  • Grammatical mood used for statement of fact

    English besides the indicative are the imperative ("Be quiet!") and the conditional ("I would be quiet") (although this is not always analyzed as a mood)

    Realis mood

    Realis_mood

  • Bootstrapping (statistics)
  • Statistical method

    \right)\right|\to 0{\text{ in probability as }}n\to \infty ,} where P ∗ {\displaystyle P^{*}} represents probability conditional on X n 1 , … , X n n {\displaystyle

    Bootstrapping (statistics)

    Bootstrapping_(statistics)

  • Parametric statistics
  • Branch of statistics

    provide methods to systematically analyse data and infer properties of the probability distribution from which the data was drawn. The fundamental assumption

    Parametric statistics

    Parametric_statistics

  • Haar measure
  • Left-invariant (or right-invariant) measure on locally compact topological group

    analysis, number theory, group theory, representation theory, statistics, probability theory, and ergodic theory. Let ( G , ⋅ ) {\displaystyle (G,\cdot )}

    Haar measure

    Haar_measure

  • Mathematical linguistics
  • Branch of applied mathematics

    between words can be determined based on whether a pair of words satisfies conditional propositions. Methods of formal linguistics were introduced by semioticians

    Mathematical linguistics

    Mathematical linguistics

    Mathematical_linguistics

  • Maxwell's theorem
  • Concept in probability theory

    In probability theory, Maxwell's theorem (known also as Herschel-Maxwell's theorem and Herschel-Maxwell's derivation) states that if the probability distribution

    Maxwell's theorem

    Maxwell's_theorem

  • Glossary of mathematical symbols
  • field E. 4.  In probability theory, denotes a conditional probability. For example, P ( A / B ) {\displaystyle P(A/B)} denotes the probability of A, given

    Glossary of mathematical symbols

    Glossary_of_mathematical_symbols

  • History of statistics
  • are often associated with models expressed using probabilities, hence the connection with probability theory. The large requirements of data processing

    History of statistics

    History_of_statistics

  • Multivariate t-distribution
  • Multivariable generalization of the Student's t-distribution

    t-distribution (or multivariate Student distribution) is a multivariate probability distribution. It is a generalization to random vectors of the Student's

    Multivariate t-distribution

    Multivariate_t-distribution

  • List of disorder prediction software
  • (June 2008). "OnD-CRF: predicting order and disorder in proteins using conditional random fields". Bioinformatics. 24 (11): 1401–2. doi:10.1093/bioinformatics/btn132

    List of disorder prediction software

    List_of_disorder_prediction_software

  • Occam's razor
  • Philosophical problem-solving principle

    concepts in Bayesian inference (namely marginal probability, conditional probability, and posterior probability). The bias–variance tradeoff is a framework

    Occam's razor

    Occam's razor

    Occam's_razor

  • Dempster–Shafer theory
  • Mathematical framework to model epistemic uncertainty

    Bel(red)+Bel(green) does not have to equal Bel(red or green). Thus, Bayes' conditional probability can be considered as a special case of Dempster's rule of combination

    Dempster–Shafer theory

    Dempster–Shafer theory

    Dempster–Shafer_theory

  • Maximal entropy random walk
  • Type of biased random walk on a graph

    by the probability of being at the i {\displaystyle i} -th vertex, i.e. ρ i {\displaystyle \rho _{i}} , gives for the conditional probability S i j {\displaystyle

    Maximal entropy random walk

    Maximal_entropy_random_walk

  • Moving average
  • Type of statistical measure over subsets of a dataset

    normally distributed. However, the normal distribution does not place high probability on very large deviations from the trend which explains why such deviations

    Moving average

    Moving average

    Moving_average

  • Vertical bar
  • Typographic symbol

    used singly in many different ways: conditional probability: P ( X | Y ) {\displaystyle P(X|Y)} , read "the probability of X given Y" distance: P | a b {\displaystyle

    Vertical bar

    Vertical_bar

  • 2012 NBA draft
  • 66th edition of the draft

    international players. The New Orleans Hornets, who had a 13.70 percent probability of obtaining the first selection, won the NBA draft lottery on May 30

    2012 NBA draft

    2012_NBA_draft

  • The XYY Man
  • British television series

    there is no connection. An early academic paper studying the conditional probability fallacy resulted in the myth becoming conventional wisdom in the

    The XYY Man

    The_XYY_Man

  • Partial correlation
  • Concept in probability theory and statistics

    In probability theory and statistics, partial correlation measures the degree of association between two random variables, with the effect of a set of

    Partial correlation

    Partial_correlation

  • 2015 NBA draft
  • Basketball player selection

    L.A. Lakers acquired Jeremy Lin, a conditional 2015 first-round pick (protected top 14 in 2014) and a conditional 2015 second-round pick Houston acquired

    2015 NBA draft

    2015_NBA_draft

  • Hoshen–Kopelman algorithm
  • Algorithm for labeling clusters on a grid

    lattice where each cell can be occupied with the probability p and can be empty with the probability 1 – p. Each group of neighboring occupied cells forms

    Hoshen–Kopelman algorithm

    Hoshen–Kopelman_algorithm

  • Pattern recognition
  • Automated recognition of patterns and regularities in data

    inverse probability p ( x | l a b e l ) {\displaystyle p({{\boldsymbol {x}}|{\rm {label}}})} is instead estimated and combined with the prior probability p

    Pattern recognition

    Pattern_recognition

  • Fisher information
  • Notion in statistics

    the probability of X {\displaystyle X} depends. Let f ( X ; θ ) {\displaystyle f(X;\theta )} be the probability density function (or probability mass

    Fisher information

    Fisher information

    Fisher_information

  • Coin flipping
  • Practice of throwing a coin in the air to choose between two alternatives

    land on a particular face.[citation needed] Human intuition about conditional probability is often very poor (see gambler's fallacy) and can give rise to

    Coin flipping

    Coin flipping

    Coin_flipping

  • Bayesian inference in marketing
  • Application of statistical methods to marketing processes

    the posterior probability of the hypothesis is equal to the prior probability of the hypothesis multiplied by the conditional probability of the evidence

    Bayesian inference in marketing

    Bayesian inference in marketing

    Bayesian_inference_in_marketing

  • McNemar's test
  • Statistical test used on paired nominal data

    p_{c}\end{aligned}}} Here pa, etc., denote the theoretical probability of occurrences in cells with the corresponding label. The McNemar test

    McNemar's test

    McNemar's_test

  • Logarithmically concave function
  • Type of mathematical function

    maximum entropy probability distribution with specified mean μ and Deviation risk measure D. As it happens, many common probability distributions are

    Logarithmically concave function

    Logarithmically_concave_function

  • Replication crisis
  • Observed inability to reproduce scientific studies

    D} , the corresponding p-value is the probability that the test statistic is at least as extreme, conditional on H 0 {\displaystyle H_{0}} . For example

    Replication crisis

    Replication crisis

    Replication_crisis

  • 2014 NBA draft
  • Basketball player selection

    Nikola Vučević and a conditional 2015 first-round pick from Philadelphia Orlando acquired Josh McRoberts, Christian Eyenga, a conditional 2017 first-round

    2014 NBA draft

    2014_NBA_draft

  • Lindy effect
  • Theorized increase of longevity with age

    Mathematically, the Lindy effect corresponds to lifetimes following a Pareto probability distribution. The concept is named after Lindy's delicatessen in New

    Lindy effect

    Lindy_effect

  • English modal auxiliary verbs
  • Class of auxiliary verbs in English that lack untensed forms

    do so (I helped move the piano). An apodosis is the "then" half of a conditional statement. (The "if" half is the protasis.) Remote here means "thought

    English modal auxiliary verbs

    English modal auxiliary verbs

    English_modal_auxiliary_verbs

  • Point estimation
  • Parameter estimation via sample statistics

    said to be sufficient for θ (or for the family of distribution) if the conditional distribution of X given T is free from θ. Often, one is interested in

    Point estimation

    Point_estimation

  • Pearson's chi-squared test
  • Evaluates how likely it is that any difference between data sets arose by chance

    then the maximum likelihood estimate for the population probability is the observed probability, and one may compute a credible region around this or another

    Pearson's chi-squared test

    Pearson's_chi-squared_test

  • Joint Entrance Examination – Advanced
  • Indian academic examination

    linear algebra), combinatorics, probability (including topics like conditional probability, law of total probability, Bayes' theorem), geometry, coordinate

    Joint Entrance Examination – Advanced

    Joint Entrance Examination – Advanced

    Joint_Entrance_Examination_–_Advanced

  • Principal component analysis
  • Method of data analysis

    identify the specific properties of a stimulus that increases a neuron's probability of generating an action potential. This technique is known as spike-triggered

    Principal component analysis

    Principal component analysis

    Principal_component_analysis

  • Mean-field particle methods
  • Probabilistic problem-solving algorithms

    Using the tower property of conditional expectations we prove that the probability distributions η n {\displaystyle \eta _{n}} satisfy

    Mean-field particle methods

    Mean-field_particle_methods

  • Point process
  • Random set of points on a space with random number and random position

    In statistics and probability theory, a point process or point field is a set of a random number of mathematical points randomly located on a mathematical

    Point process

    Point_process

  • Time series
  • Sequence of data points over time

    over time (heteroskedasticity). These models represent autoregressive conditional heteroskedasticity (ARCH) and the collection comprises a wide variety

    Time series

    Time series

    Time_series

  • Outline of machine learning
  • Overview of and topical guide to machine learning

    Inauthentic text Incremental decision tree Induction of regular languages Inductive bias Inductive probability Inductive programming Influence diagram Information

    Outline of machine learning

    Outline_of_machine_learning

  • Auction theory
  • Branch of economics

    or "buyer surplus" is P(v), the probability of being the winner. In every participant-efficient auction, the probability of winning is 1 for a high-valuation

    Auction theory

    Auction_theory

  • Partially observable Markov decision process
  • Generalization of a Markov decision process

    to be equal to the set of states and defining the observation conditional probabilities to deterministically select the observation that corresponds to

    Partially observable Markov decision process

    Partially_observable_Markov_decision_process

  • Belief
  • Subjective attitude that something is true

    subjective probability value. The subjective probability model posits that these subjective probabilities follow the same rules as objective probabilities. For

    Belief

    Belief

  • Quantum logic
  • Theory of logic to account for observations from quantum theory

    quantum logic as a basis for reasoning, because it lacks a material conditional; a common alternative is the system of linear logic, of which quantum

    Quantum logic

    Quantum_logic

  • 2016 NBA draft
  • Basketball player selection

    Timberwolves) Philadelphia acquired Luc Mbah a Moute, Alexey Shved, and Miami's conditional first round pick Cleveland acquired Kevin Love Minnesota acquired Andrew

    2016 NBA draft

    2016_NBA_draft

  • Variance function
  • Smooth function in statistics

    variable y {\displaystyle {\textit {y}}} in the exponential family has a probability density function of the form, f ( y , θ , ϕ ) = exp ⁡ ( y θ − b ( θ )

    Variance function

    Variance_function

  • Gleason's theorem
  • Theorem in quantum mechanics

    physics, Gleason's theorem shows that the rule one uses to calculate probabilities in quantum physics, the Born rule, can be derived from the usual mathematical

    Gleason's theorem

    Gleason's_theorem

  • Founders of statistics
  • from the History of Probability and Statistics. University of Southampton. "Francis Galton". Figures from the History of Probability and Statistics. University

    Founders of statistics

    Founders_of_statistics

  • 2022 NBA draft
  • 76th edition of the draft

    Matthew Dellavedova, John Henson, 2021 and 2022 second-round picks, and a conditional first-round pick Milwaukee acquired George Hill, Jason Smith, a 2020

    2022 NBA draft

    2022_NBA_draft

  • Kalman filter
  • Algorithm that estimates unknowns from a series of measurements over time

    Physics, 5:11, pp. 1–19. Stratonovich, R. L. (1960). Conditional Markov Processes. Theory of Probability and Its Applications, 5, pp. 156–178. Stepanov, O

    Kalman filter

    Kalman filter

    Kalman_filter

  • Index of dispersion
  • Normalized measure of the dispersion of a probability distribution

    In probability theory and statistics, the index of dispersion, dispersion index, coefficient of dispersion, relative variance, or variance-to-mean ratio

    Index of dispersion

    Index_of_dispersion

  • 2023 NBA draft
  • 77th edition of the NBA draft

    Washington Wizards Washington acquired Ish Smith, Vernon Carey Jr., and a conditional second-round draft pick in 2023 or 2024 originally from Boston Charlotte

    2023 NBA draft

    2023_NBA_draft

  • Radioisotope thermoelectric generator
  • Electrical generator that uses heat from radioactive decay

    tables of safety analysis results, Table D-1 on page D-4, see conditional probability column for GPHS-RTG Physical, Nuclear, and Chemical, Properties

    Radioisotope thermoelectric generator

    Radioisotope thermoelectric generator

    Radioisotope_thermoelectric_generator

  • Thought
  • Cognitive process independent of the senses

    this wider sense, the term "subjunctive conditional" is sometimes used instead of "counterfactual conditional". But the paradigmatic cases of counterfactual

    Thought

    Thought

    Thought

  • Outline of computer programming
  • Overview of and topical guide to computer programming

    loops While loops Conditionals If-then If-then-else Case and switch statements Control flow Data structures Objects Arrays Regular expressions Programming

    Outline of computer programming

    Outline_of_computer_programming

  • Data validation
  • Process of ensuring computer data is both correct and useful

    complex processing. Such complex processing may include the testing of conditional constraints for an entire complex data object or set of process operations

    Data validation

    Data_validation

  • Xeroderma pigmentosum
  • Medical condition multisystem disorder

    and psychological support is appropriate for the families to discuss probability of occurrence in future pregnancies, feelings of isolation and concern

    Xeroderma pigmentosum

    Xeroderma pigmentosum

    Xeroderma_pigmentosum

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REGULAR CONDITIONAL-PROBABILITY

  • Inconditional
  • a.

    Unconditional.

  • Conditionate
  • v. t.

    Conditional.

  • Regular
  • a.

    Governed by rule or rules; steady or uniform in course, practice, or occurence; not subject to unexplained or irrational variation; returning at stated intervals; steadily pursued; orderlly; methodical; as, the regular succession of day and night; regular habits.

  • Conditional
  • n.

    A conditional word, mode, or proposition.

  • Conditionate
  • v. t.

    To qualify by conditions; to regulate.

  • Unconditional
  • a.

    Not conditional limited, or conditioned; made without condition; absolute; unreserved; as, an unconditional surrender.

  • Irregular
  • a.

    Not regular; not conforming to a law, method, or usage recognized as the general rule; not according to common form; not conformable to nature, to the rules of moral rectitude, or to established principles; not normal; unnatural; immethodical; unsymmetrical; erratic; no straight; not uniform; as, an irregular line; an irregular figure; an irregular verse; an irregular physician; an irregular proceeding; irregular motion; irregular conduct, etc. Cf. Regular.

  • Conditionate
  • v. t.

    To put under conditions; to render conditional.

  • Regular
  • a.

    Having all the parts of the same kind alike in size and shape; as, a regular flower; a regular sea urchin.

  • Conditional
  • a.

    Expressing a condition or supposition; as, a conditional word, mode, or tense.

  • Conditional
  • a.

    Containing, implying, or depending on, a condition or conditions; not absolute; made or granted on certain terms; as, a conditional promise.

  • Regular
  • a.

    Conformed to a rule; agreeable to an established rule, law, principle, or type, or to established customary forms; normal; symmetrical; as, a regular verse in poetry; a regular piece of music; a regular verb; regular practice of law or medicine; a regular building.

  • Irregular
  • n.

    One who is not regular; especially, a soldier not in regular service.

  • Conditionly
  • adv.

    Conditionally.

  • Unconditioned
  • a.

    Not conditioned or subject to conditions; unconditional.

  • Regular
  • a.

    Thorough; complete; unmitigated; as, a regular humbug.

  • Regular
  • a.

    Constituted, selected, or conducted in conformity with established usages, rules, or discipline; duly authorized; permanently organized; as, a regular meeting; a regular physican; a regular nomination; regular troops.

  • Regular
  • a.

    Belonging to a monastic order or community; as, regular clergy, in distinction dfrom the secular clergy.

  • Conditionally
  • adv.

    In a conditional manner; subject to a condition or conditions; not absolutely or positively.

  • Condition
  • n.

    To invest with, or limit by, conditions; to burden or qualify by a condition; to impose or be imposed as the condition of.