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Probability theory concept
hypothesis. It is the opposite of conditional dependence. Conditional independence is usually formulated in terms of conditional probability, as a special case
Conditional_independence
When the occurrence of one event does not affect the likelihood of another
\!\!\perp B} , where the latter symbol often is also used for conditional independence) if and only if their joint probability equals the product of their
Independence (probability theory)
Independence_(probability_theory)
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
Concept in probability theory
dependent conditional on C . {\displaystyle C.} Conditional independence – Probability theory concept de Finetti's theorem – Conditional independence of exchangeable
Conditional_dependence
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
Concept in probability theory
probability is a fundamental rule relating marginal probabilities to conditional probabilities. It expresses the total probability of an outcome which
Law_of_total_probability
Probabilistic graphical representation of causal relationships
probabilistic graphical model that represents a set of variables and their conditional dependencies via a directed acyclic graph (DAG). While it is one of several
Bayesian_network
Type of probability distribution
{\displaystyle P(B)} and P ( A ∣ B ) {\displaystyle P(A\mid B)} . Such conditional independence relations can be represented with a Bayesian network or copula
Joint probability distribution
Joint_probability_distribution
Concept in probability theory and statistics
Masaaki Sibuya (2004). "Partial correlation and conditional correlation as measures of conditional independence". Australian and New Zealand Journal of Statistics
Partial_correlation
Symbol used in mathematics and logic
U+2AEB in Unicode) is a binary relation symbol used to represent: Conditional independence of random variables in probability theory Alternative plus sign
Up_tack
Foundations of probability theory
mathematical setsPages displaying short descriptions of redirect targets Conditional probability – Probability of an event occurring, given that another event
Probability_axioms
Types of numerical variables in mathematics
event Joint probability Marginal probability Conditional probability Independence Conditional independence Law of total probability Law of large numbers
Continuous or discrete variable
Continuous_or_discrete_variable
Graphoid math statements
"graphoids" after discovering that a set of axioms that govern conditional independence in probability theory is shared by undirected graphs. Variables
Graphoid
Subset of variables that contains all the useful information
minimal—meaning that no variable in it can be removed without losing this conditional independence—it is called a Markov boundary. Identifying a Markov blanket or
Markov_blanket
Mathematical theory of majority voting
assumptions - conditional independence and conditional competence - are not justifiable simultaneously (under the same conditionalization). A possible
Jury_theorem
Any experiment with two possible random outcomes
event Joint probability Marginal probability Conditional probability Independence Conditional independence Law of total probability Law of large numbers
Bernoulli_trial
System in which no randomness is involved in determining its future states
event Joint probability Marginal probability Conditional probability Independence Conditional independence Law of total probability Law of large numbers
Deterministic_system
Number measuring the chance an event occurs
number of events. Conditional probability is the probability of some event A, given the occurrence of some other event B. Conditional probability is written
Probability
Conditional independence of exchangeable observations
means Xi=1. The independence asserted here is conditional independence, i.e. the Bernoulli random variables in the sequence are conditionally independent
De_Finetti's_theorem
Measure of total value one, generalizing probability distributions
4 , {\displaystyle 1/4+1/2=3/4,} as in the diagram on the right. The conditional probability based on the intersection of events defined as: μ ( B ∣ A
Probability_measure
Probability distribution
((1/p1) − 1)/n + ((1/p2) − 1)/m. If X ~ B(n, p) and Y | X ~ B(X, q) (the conditional distribution of Y, given X), then Y is a simple binomial random variable
Binomial_distribution
Averages of repeated trials converge to the expected value
\sin(X)e^{X}X^{-1}} has no expected value according to Lebesgue integration, but using conditional convergence and interpreting the integral as a Dirichlet integral, which
Law_of_large_numbers
Statistical tool to model changing systems
Model. Both have been used for behavior recognition and certain conditional independence properties between different levels of abstraction in the model
Markov_model
Diagram to represent a probability space in probability theory
represent a series of independent events (such as a set of coin flips) or conditional probabilities (such as drawing cards from a deck, without replacing the
Tree diagram (probability theory)
Tree_diagram_(probability_theory)
Observed value of a random variable
event Joint probability Marginal probability Conditional probability Independence Conditional independence Law of total probability Law of large numbers
Realization_(probability)
d-separations in the graph also correspond to conditional independence relations. This also means that a node is conditionally independent of the entire network,
Causal_Markov_condition
Directed graph that models causal relationships between variables
without correlated error terms (sometimes called Markovian), these conditional independences represent all of the model's testable implications. Suppose we
Causal_graph
Random process independent of past history
that could be made knowing the process's full history. In other words, conditional on the present state of the system, its future and past states are independent
Markov_chain
Statistical estimator
distributions, sparsity in the precision matrix corresponds to conditional independence between the variables therefore implying a Gaussian graphical model
Graphical_lasso
Assumptions for inference in machine learning
algorithms. Maximum conditional independence: if the hypothesis can be cast in a Bayesian framework, try to maximize conditional independence. This is the bias
Inductive_bias
In statistics and probability theory, set of outcomes to which a probability is assigned
subsets. For the standard tools of probability theory, such as joint and conditional probabilities, to work, it is necessary to use a σ-algebra, that is,
Event_(probability_theory)
Mathematical concept
definition of probability spaces gives rise to the natural concept of conditional probability. Every set A with non-zero probability (that is, P(A) > 0)
Probability_space
2000 book by Judea Pearl
set of parent causes of two variables induces a relationship of conditional independence between them. Through this means Hoover argues, Pearl develop(s)
Causality_(book)
Probability distribution modeling a coin toss which need not be fair
event Joint probability Marginal probability Conditional probability Independence Conditional independence Law of total probability Law of large numbers
Bernoulli_distribution
identically-distributed random variables Statistical independence Conditional independence Pairwise independence Covariance Covariance matrix De Finetti's theorem
List_of_probability_topics
Randomly determined process
event Joint probability Marginal probability Conditional probability Independence Conditional independence Law of total probability Law of large numbers
Stochastic
Process forming a path from many random steps
E(S_{n})=\sum _{j=1}^{n}E(Z_{j})=0.} A similar calculation, using the independence of the random variables and the fact that E ( Z n 2 ) = 1 {\displaystyle
Random_walk
Computational problems no algorithm can solve
(2023). "Undecidability of Network Coding, Conditional Information Inequalities, and Conditional Independence Implication". IEEE Transactions on Information
List_of_undecidable_problems
Subset of artificial intelligence
graphical model that represents a set of random variables and their conditional independence with a directed acyclic graph (DAG). For example, a Bayesian network
Machine_learning
Probability distribution
would like to capture this dependence. This suggests that we create a conditional prior of the mean on the unknown variance, with a hyperparameter specifying
Normal_distribution
Procedure that can be infinitely repeated, with a well-defined set of outcomes
event Joint probability Marginal probability Conditional probability Independence Conditional independence Law of total probability Law of large numbers
Experiment (probability theory)
Experiment_(probability_theory)
Graphical tool in probability
vine is a special case for which all constraints are two-dimensional or conditional two-dimensional. Regular vines generalize trees, and are themselves specializations
Vine_copula
Opposite of a probability event
event Joint probability Marginal probability Conditional probability Independence Conditional independence Law of total probability Law of large numbers
Complementary_event
Topics referred to by the same term
CodeIgniter, a PHP framework Cirrus cloud Convective instability Conditional independence, a type of relation of random variables in probability theory Confidence
CI
Overview of and topical guide to probability
probability Frequency probability Conditional probability The law of total probability Bayes' theorem Independence (probability theory) (Related topics:
Outline_of_probability
Possible result of an experiment or trial
event Joint probability Marginal probability Conditional probability Independence Conditional independence Law of total probability Law of large numbers
Outcome_(probability)
Hidden Markov model algorithm
{\displaystyle t} . Instead, the forward algorithm takes advantage of the conditional independence rules of the hidden Markov model (HMM) to perform the calculation
Forward_algorithm
Branch of mathematics concerning probability
of probability Probability space – Mathematical concept Statistical independence – When the occurrence of one event does not affect the likelihood of
Probability_theory
Average value of a random variable
These inequalities are significant for their nearly complete lack of conditional assumptions. For example, for any random variable with finite expectation
Expected_value
Branch of pure mathematics
in number theory, illustrated by an Ulam spiral. It shows the conditional independence between being prime and being a value of certain quadratic polynomials
Number_theory
Probabilistic classification algorithm
conditional independence assumptions come into play: assume that all features in x {\displaystyle \mathbf {x} } are mutually independent, conditional
Naive_Bayes_classifier
1919 war between the British Empire (India) and the Emirate of Afghanistan
following his declaration of independence, rather than waging war, they would likely have conceded some form of conditional independence, as they had previously
Third_Anglo-Afghan_War
Topics referred to by the same term
geometric algebra, extensions of the inner product One of the rules of conditional independence, in probability Contraction (logic), a structural rule in proof
Contraction
Diagram that shows all possible logical relations between a collection of sets
event Joint probability Marginal probability Conditional probability Independence Conditional independence Law of total probability Law of large numbers
Venn_diagram
Automatic conversion of spoken language into text
however, it is incapable of learning the language model due to conditional independence assumptions, similar to an HMM. Consequently, CTC models can directly
Speech_recognition
Set of all possible outcomes or results of a statistical trial or experiment
event Joint probability Marginal probability Conditional probability Independence Conditional independence Law of total probability Law of large numbers
Sample_space
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
Set of events whose union covers the entire sample space
event Joint probability Marginal probability Conditional probability Independence Conditional independence Law of total probability Law of large numbers
Collectively exhaustive events
Collectively_exhaustive_events
known, it may still appear as a latent variable in the model. Conditional independence Lazarsfeld, P.F., and Henry, N.W. (1968) Latent Structure analysis
Local_independence
Stochastic process with discrete movements
event Joint probability Marginal probability Conditional probability Independence Conditional independence Law of total probability Law of large numbers
Jump_process
Study of uncertainty in the output of a mathematical model or system
such as noisy models. Noisy models exploit information on the conditional independence between variables to significantly reduce dimensionality. The use
Sensitivity_analysis
Inequality applying to probability spaces
event Joint probability Marginal probability Conditional probability Independence Conditional independence Law of total probability Law of large numbers
Boole's_inequality
Random variable with multiple component dimensions
variables X i {\displaystyle X_{i}} are called marginal distributions. The conditional probability distribution of X i {\displaystyle X_{i}} given X j {\displaystyle
Multivariate_random_variable
Referendum held in Scotland
(in the event of Scottish independence) it should remain in the UK. The third option would have implemented a conditional promise made in 2012 by an
2014 Scottish independence referendum
2014_Scottish_independence_referendum
Logical connective
The material conditional (also known as material implication) is a binary operation commonly used in logic. When the conditional symbol → {\displaystyle
Material_conditional
Event that contains only one outcome
event Joint probability Marginal probability Conditional probability Independence Conditional independence Law of total probability Law of large numbers
Elementary_event
Table that displays the frequency of variables
contained in high-dimensional contingency tables. If some of the conditional independences are revealed, then even the storage of the data can be done in
Contingency_table
Category whose objects are measurable spaces and whose morphisms are measurable maps
Fritz, Tobias (2020). "A synthetic approach to Markov kernels, conditional independence and theorems on sufficient statistics". Advances in Mathematics
Category_of_measurable_spaces
Mathematical function for the probability a given outcome occurs in an experiment
underlying distribution of the individual variables. Mathematics portal Conditional probability distribution Empirical probability distribution Histogram
Probability_distribution
Movement to end British rule in India
The Indian independence movement was a series of political efforts from mid-1880s to 1947, that took place in the Indian subcontinent with the aim of ending
Indian_independence_movement
Random process of binary (boolean) random variables
a sequence of independent identically distributed Bernoulli trials. Independence of the trials implies that the process is memoryless, in which past event
Bernoulli_process
Statistical concept
(an R package is available for a subset of these), as well as conditional independence testing under a model-X assumption. However, in many other statistical
E-values
Collection of random variables
given the current value and all the past values of the process, the conditional expectation of every future value is equal to the current value. In discrete
Stochastic_process
1016/B978-1-4832-1451-1.50052-4. ISBN 9781483214511. S2CID 14690613. M. Studeny: On mathematical description of probabilistic conditional independence structures
Moral_graph
the conditional density of V given Z. Now, suppose that given Z, V is conditionally independent of W. This is called the conditional independence assumption
Two-step_M-estimator
Philosophical view that events are determined by prior events
event Joint probability Marginal probability Conditional probability Independence Conditional independence Law of total probability Law of large numbers
Determinism
Paradigm for the design, analysis, and scoring of tests
class analysis with dichotomous or ordered category measures: conditional independence/dependence models". Applied Psychological Measurement. 23 (4):
Item_response_theory
Class of nonparametric methods
Gretton, X. Sun, and B. Schölkopf (2008). Kernel measures of conditional independence. Advances in Neural Information Processing Systems 20, MIT Press
Kernel embedding of distributions
Kernel_embedding_of_distributions
form of a directed acyclic graph. Ancestral graphs can encode conditional independence relations that arise in directed acyclic graph (DAG) models with
Ancestral_graph
Class of statistical models
probability tree). A staged tree places equality relationships on the conditional probability distributions of an event tree. These equality relationships
Staged_tree_(mathematics)
Variable representing a random phenomenon
construct them, and to define notions such as correlation and dependence or independence based on a joint distribution of two or more random variables on the
Random_variable
Statistics concept
\pi \right)\end{aligned}}} Conditional independence hypotheses then allow further simplifications. A conditional independence hypothesis for variable L
Bayesian_programming
Set of learning techniques in machine learning
on the visible (hidden) variables.[clarification needed] Such conditional independence facilitates computations. An RBM can be viewed as a single layer
Feature_learning
Concept in probability theory and statistics
event Joint probability Marginal probability Conditional probability Independence Conditional independence Law of total probability Law of large numbers
Complex_random_variable
Apparent lack of pattern or predictability in events
event Joint probability Marginal probability Conditional probability Independence Conditional independence Law of total probability Law of large numbers
Randomness
Philosophical concept
event Joint probability Marginal probability Conditional probability Independence Conditional independence Law of total probability Law of large numbers
Indeterminism
event Joint probability Marginal probability Conditional probability Independence Conditional independence Law of total probability Law of large numbers
Pairwise_error_probability
Category whose objects are measurable spaces and whose morphisms are Markov kernels
Fritz, Tobias (2020). "A synthetic approach to Markov kernels, conditional independence and theorems on sufficient statistics". Advances in Mathematics
Category_of_Markov_kernels
British professor of Political Economy and Econometrics
hdl:10044/1/41334. Linton, Oliver; Gozalo, Pedro (August 2014). "Testing conditional independence restrictions". Econometric Reviews. 33 (5–6): 523–552. doi:10.1080/07474938
Oliver_Linton
Mathematical theorem
that: A , B ⊥ E , F | C , D {\displaystyle A,B\perp E,F|C,D} (see conditional independence), since C , D {\displaystyle C,D} forms a barrier between A , B
Hammersley–Clifford_theorem
Analysis of datasets using techniques from topology
tools quantifies statistical dependences and independences, including Markov chains and conditional independence, in the multivariate case. Notably, mutual-informations
Topological_data_analysis
Analytical expression in statistics
Field (GMRF) (that is, a multivariate Gaussian with additional conditional independence properties) with probability density π ( x | θ ) ∝ | Q θ | 1 /
Laplace's_approximation
Abstract structure modeling spaces of probability measures
Fritz, Tobias (2020). "A synthetic approach to Markov kernels, conditional independence and theorems on sufficient statistics". Advances in Mathematics
Giry_monad
Crimea under direct Ukrainian administration
the first Crimean constitution together with a declaration of conditional independence on the same day. There was stiff resistance from Ukraine and a
History_of_Crimea_(1991–2014)
Problem in machine learning and statistical classification
perform well in spite of the underlying simplifying assumption of conditional independence. Decision tree learning is a powerful classification technique
Multiclass_classification
Multivariate continuous probability distribution
(2020-12-01). "Bayesian hypothesis testing for Gaussian graphical models: Conditional independence and order constraints". Journal of Mathematical Psychology. 99
Matrix_F-distribution
Statistical principle
Zbl 0485.62004. Nogales, A.G.; Oyola, J.A.; Perez, P. (2000). "On conditional independence and the relationship between sufficiency and invariance under the
Sufficient_statistic
Two propositions or events that cannot both be true
event Joint probability Marginal probability Conditional probability Independence Conditional independence Law of total probability Law of large numbers
Mutual_exclusivity
Task of finding records in a data set that refer to same entity across different sources
estimate the conditional probabilities required by the Fellegi-Sunter theory. Several researchers have reported that the conditional independence assumption
Record_linkage
Graphical representation of a morphism
Tobias (August 2020). "A synthetic approach to Markov kernels, conditional independence and theorems on sufficient statistics". Advances in Mathematics
String_diagram
CONDITIONAL INDEPENDENCE
CONDITIONAL INDEPENDENCE
Girl/Female
Tamil
Circumstance, Period of life, Wick, Condition, Degree
Boy/Male
Bengali, Indian
Sleepless; Condition of Being Awake; One who Conquers Sleep
Surname or Lastname
Irish
Irish : reduced Anglicized form of Gaelic Ó Loingsigh ‘descendant of Loingseach’, a personal name meaning ‘mariner’ (from long ‘ship’). This is now a common surname in Ireland but of different local origins, for example chieftain families in counties Antrim and Tipperary, while in Ulster and Connacht there were families called Ó Loingseacháin who later shortened their name to Ó Loingsigh and also Anglicized it as Lynch.Irish (Anglo-Norman) : Anglicized form of Gaelic Linseach, itself a Gaelicized form of Anglo-Norman French de Lench, the version found in old records. This seems to be a local name, but its origin is unknown. One family of bearers of this name was of Norman origin, but became one of the most important tribes of Galway.English : topographic name for someone who lived on a slope or hillside, Old English hlinc, or perhaps a habitational name from Lynch in Dorset or Somerset or Linch in Sussex, all named with this word.This name was brought independently from Ireland to North America by many bearers. Jonack Lynch emigrated from Ireland to SC shortly after the first settlement of that colony in 1670. His grandson Thomas Lynch, born in 1727 in Berkeley Co., SC, was a member of both Continental Congresses, and his great-grandson, also called Thomas Lynch, born 1749 in Winyaw, SC, was a signer of the Declaration of Independence.
Surname or Lastname
English
English : patronymic from Jeffrey.The third U.S. president, author of the Declaration of Independence, and VA statesman Thomas Jefferson relates in his memoirs a family tradition that he was descended from Welsh stock on his father’s side, while noting the relative infrequency of the name Jefferson in Wales. It is a characteristically northern English name. A Jefferson was among the burgesses who attended the first representative assembly at Jamestown, VA, in 1619.
Boy/Male
African, Arabic, Australian, Greek, Swahili
Unique; Graceful; Kind; Sweet; The Beautiful Ocean; Loving; Forgiving; Content; Delighted; Beauty; Perfect; State; Handsome; Condition; The Sea
Surname or Lastname
English (Kent)
English (Kent) : apparently a habitational name from a lost or unidentified place, possibly so named from Old English gÄra ‘triangular piece of land’ + hÄm ‘homestead’.Born in England, John Gorham emigrated to MA and in 1643 married Desire Howland, daughter of John Howland, who came to America on the Mayflower. His descendant Nathaniel (1738–96) was born in Charlestown, MA, and was one of the signers of the Declaration of Independence.
Surname or Lastname
English and Scottish
English and Scottish : occupational name for a stonemason, Middle English, Old French mas(s)on. Compare Machen. Stonemasonry was a hugely important craft in the Middle Ages.Italian (Veneto) : from a short form of Masone.French : from a regional variant of maison ‘house’.George Mason (1725–92), the American colonial statesman who framed the VA Bill of Rights and Constitution, which was used as a model by Thomas Jefferson when drafting the Declaration of Independence, was a VA planter, fourth in descent from George Mason (?1629–?86), a royalist soldier of the English Civil War who had received land grants in VA. As well as being prominent in the affairs of VA, the family also produced the first governor of MI.
Girl/Female
Hindu
Good or Happy condition, Solution, Fortune
Girl/Female
Tamil
Good or Happy condition, Solution
Surname or Lastname
English
English : from the Middle English personal name Hann + the hypocoristic suffix -cok, which was commonly added to personal names (see Cocke).Dutch : from Middle Dutch hanecoc ‘winkle’, ‘periwinkle’ (a type of shellfish), probably a metonymic occupational name for someone who gathered and sold shellfish.Thomas Hancock, the uncle of Declaration of Independence signatory John Hancock (1736/7–93), was among the foremost of 18th-century American businessmen. He was a descendant of Nathaniel Hancock, who was known to have been in Cambridge, MA, as early as 1634. Born in Braintree, MA, John Hancock was president of the Second Continental Congress and the first governor of the state of MA.
Boy/Male
African, Arabic, Australian, French, Indian, Muslim, Sindhi
Sacrifice; Unconditional Love; Love
Boy/Male
Tamil
Can travel in all climatic conditions
Girl/Female
Tamil
Good or Happy condition, Solution, Fortune
Girl/Female
Indian
Circumstance, Period of life, Wick, Condition, Degree
Surname or Lastname
English
English : habitational name from any of several places so called, named with the genitive plural huntena of Old English hunta ‘hunter’ + tūn ‘enclosure’, ‘settlement’ or dūn ‘hill’ (the forms in -ton and -don having become inextricably confused). A number of bearers of this name may well derive it from Huntingdon, now in Cambridgeshire (formerly the county seat of the old county of Huntingdonshire), which is named from the genitive case of Old English hunta ‘huntsman’, perhaps used as a personal name, + dūn ‘hill’.A prominent American family of this name were founded by Simon Huntington, who himself never saw the New World, for he died in 1633 on the voyage to Boston, where his widow settled with her children. Their descendants include Jabez Huntington (1719–86), a wealthy West Indies trader, and Samuel Huntington (1731–96), who was one of the signers of the Declaration of Independence. Collis Potter Huntington (1821–1900) was an American railway magnate. Beginning with little education or money, he made a huge fortune, some of which he left to his nephew, Henry Huntington (1850–1927), who used the money to establish the Huntington library and art gallery in CA.
Boy/Male
Indian
Can Travel in All Climatic Conditions
Boy/Male
Arabic
State; Condition
Boy/Male
Sikh
Self-rule, Independence
Girl/Female
Hindu
Good or Happy condition, Solution
Surname or Lastname
English
English : variant of Hillary.William Ellery, a signer of the Declaration of Independence, was born in Newport, RI, in 1727.
CONDITIONAL INDEPENDENCE
CONDITIONAL INDEPENDENCE
Girl/Female
British, Dutch, English
Bright
Girl/Female
Tamil
Sowmiya | ஸோவà¯à®®à¯€à®¯à®¾
Beautiful, Gentle, Soft
Boy/Male
Indian
Servant of the right-minded, Slave of the guide
Girl/Female
French, German, Teutonic
Renowned; Famous Land
Boy/Male
Muslim
Conqueror
Boy/Male
English
World guardian.
Boy/Male
Hindu
Heaven
Boy/Male
Indian, Sanskrit
Following; Carrying
Girl/Female
Indian, Telugu
Name of Flower
Boy/Male
Indian, Sanskrit
Adorable
CONDITIONAL INDEPENDENCE
CONDITIONAL INDEPENDENCE
CONDITIONAL INDEPENDENCE
CONDITIONAL INDEPENDENCE
CONDITIONAL INDEPENDENCE
adv.
Conditionally.
n.
train; acclimate.
a.
Not conditional limited, or conditioned; made without condition; absolute; unreserved; as, an unconditional surrender.
adv.
In a conditional manner; subject to a condition or conditions; not absolutely or positively.
v. t.
To put under conditions; to render conditional.
n.
To put under conditions; to require to pass a new examination or to make up a specified study, as a condition of remaining in one's class or in college; as, to condition a student who has failed in some branch of study.
v. t.
To qualify by conditions; to regulate.
a.
Unconditional.
a.
Expressing a condition or supposition; as, a conditional word, mode, or tense.
a.
Surrounded; circumstanced; in a certain state or condition, as of property or health; as, a well conditioned man.
n.
A limitation.
imp. & p. p.
of Condition
v. t.
Conditional.
n.
A conditional word, mode, or proposition.
a.
Having, or known under or by, conditions or relations; not independent; not absolute.
n.
To invest with, or limit by, conditions; to burden or qualify by a condition; to impose or be imposed as the condition of.
a.
Of the nature of a proviso; containing a proviso or condition; conditional; as, a provisory clause.
a.
Not conditioned or subject to conditions; unconditional.
a.
Containing, implying, or depending on, a condition or conditions; not absolute; made or granted on certain terms; as, a conditional promise.
v. i.
To impose upon an object those relations or conditions without which knowledge and thought are alleged to be impossible.