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Statistical model to calculate the value of multiple quantities as they change over time
Vector autoregression (VAR) is a statistical model used to capture the relationship between multiple quantities as they change over time. VAR is a type
Vector_autoregression
Statistical estimation method
statistics and econometrics, Bayesian vector autoregression (BVAR) uses Bayesian methods to estimate a vector autoregression (VAR) model. BVAR differs with standard
Bayesian vector autoregression
Bayesian_vector_autoregression
Generalization of the one-dimensional normal distribution to higher dimensions
normal distribution to higher dimensions. One definition is that a random vector is said to be k-variate normally distributed if every linear combination
Multivariate normal distribution
Multivariate_normal_distribution
Method of data analysis
space are a sequence of p {\displaystyle p} unit vectors, where the i {\displaystyle i} -th vector is the direction of a line that best fits the data
Principal_component_analysis
Measure of the joint variability
mean and the covariance matrix of the random vector X {\displaystyle \textstyle \mathbf {X} } , a vector whose jth element ( j = 1 , … , K ) {\displaystyle
Covariance
Broad concept generalizing scalars in mathematics and physics
a vector space as a codomain Vectorization (mathematics), a linear transformation that converts a matrix into a column vector Vector autoregression, an
Vector (mathematics and physics)
Vector_(mathematics_and_physics)
Statistical measure of how far values spread from their average
column vector of n {\displaystyle n} random variables X 1 , … , X n {\displaystyle X_{1},\ldots ,X_{n}} , and c {\displaystyle c} as a column vector of
Variance
Measure of variation in statistics
the standard deviation of the vector (x1, x2, x3), multiplied by the square root of the number of dimensions of the vector (3 in this case). An observation
Standard_deviation
Statistical hypothesis test for forecasting
expectations. A similar test involving more variables can be applied with vector autoregression. The validity of the Granger causality test has been challenged
Granger_causality
Simultaneous observation and analysis of more than one outcome variable
equation, with different dependent variables, estimated together. Vector autoregression involves simultaneous regressions of various time series variables
Multivariate_statistics
Statistical modeling method
assumes that the relationship between the dependent variable y and the vector of regressors x is linear. This relationship is modeled through a disturbance
Linear_regression
Measure of linear correlation
set to form the coordinates of an n-dimensional vector, and computing the cosine between these two vector directions. This expression is therefore a number
Pearson correlation coefficient
Pearson_correlation_coefficient
Correlation of a signal with a time-shifted copy of itself, as a function of shift
average model (ARIMA). With multiple interrelated data series, vector autoregression (VAR) or its extensions are used. In ordinary least squares (OLS)
Autocorrelation
Number of values in the final calculation of a statistic that are free to vary
domain of a random vector, or essentially the number of "free" components (how many components need to be known before the vector is fully determined)
Degrees of freedom (statistics)
Degrees_of_freedom_(statistics)
Statistical model used in time series analysis
(weakly) stationary stochastic process by combining two components: autoregression (AR) and moving average (MA). These models are widely used for analyzing
Autoregressive moving-average model
Autoregressive_moving-average_model
Covariance and correlation
entries of two random vectors X {\displaystyle \mathbf {X} } and Y {\displaystyle \mathbf {Y} } , while the correlations of a random vector X {\displaystyle
Cross-correlation
Numeric quantity representing the center of a collection of numbers
(Box–Jenkins) Autoregressive conditional heteroskedasticity (ARCH) Vector autoregression (VAR) (Autoregressive model (AR)) Frequency domain Spectral density
Mean
Statistical hypothesis test
one-sample multivariate test, the hypothesis is that the mean vector (μ) is equal to a given vector (μ0). The test statistic is Hotelling's t2: t 2 = n ( x
Student's_t-test
Approximation method in statistics
is an iteration number, and the vector of increments Δ β j {\displaystyle \Delta \beta _{j}} is called the shift vector. In some commonly used algorithms
Least_squares
Fundamental theorem in probability theory and statistics
i {\textstyle \mathbf {X} _{i}} is a random vector in R k {\textstyle \mathbb {R} ^{k}} , with mean vector μ = E [ X i ] {\textstyle {\boldsymbol {\mu
Central_limit_theorem
Family of probability distributions related to the normal distribution
be vector-valued such that η ( θ ) ⋅ T ( x ) {\displaystyle \eta (\theta )\cdot T(x)} is real-valued. However, see the discussion below on vector parameters
Exponential_family
Concept in probability theory and statistics
This function is used to determine the appropriate lag length for an autoregression. When the sample size is smaller than the number of variables, a.k.a
Partial_correlation
decomposition (FEVD) is used to aid in the interpretation of a vector autoregression (VAR) model once it has been fitted. The variance decomposition
Variance decomposition of forecast errors
Variance_decomposition_of_forecast_errors
Measure of covariance of components of a random vector
matrix giving the covariance between each pair of elements of a given random vector. Intuitively, the covariance matrix generalizes the notion of variance to
Covariance_matrix
Test of normality in frequentist statistics
{\displaystyle (a_{1},\dots ,a_{n})={m^{\mathsf {T}}V^{-1} \over C},} where C is a vector norm: C = ‖ V − 1 m ‖ = ( m T V − 1 V − 1 m ) 1 / 2 {\displaystyle
Shapiro–Wilk_test
Statistical property
(Box–Jenkins) Autoregressive conditional heteroskedasticity (ARCH) Vector autoregression (VAR) (Autoregressive model (AR)) Frequency domain Spectral density
Standard_error
Sequence of data points over time
acronyms are extended by including an initial "V" for "vector", as in VAR for vector autoregression. An additional set of extensions of these models is available
Time_series
Plot using the dispersal of scattered dots to show the relationship between variables
(Box–Jenkins) Autoregressive conditional heteroskedasticity (ARCH) Vector autoregression (VAR) (Autoregressive model (AR)) Frequency domain Spectral density
Scatter_plot
Measure of statistical dispersion
(Box–Jenkins) Autoregressive conditional heteroskedasticity (ARCH) Vector autoregression (VAR) (Autoregressive model (AR)) Frequency domain Spectral density
Interquartile_range
Probabilistic problem-solving algorithm
optimization. The problem is to minimize (or maximize) functions of some vector that often has many dimensions. Many problems can be phrased in this way:
Monte_Carlo_method
Method of estimating the parameters of a statistical model, given observations
probability. We write the parameters governing the joint distribution as a vector θ = [ θ 1 , θ 2 , … , θ k ] T {\displaystyle \;\theta =\left[\theta _{1}
Maximum_likelihood_estimation
Statistics concept
{X} } , a response vector y → {\displaystyle {\vec {y}}} , a parameter vector β → {\displaystyle {\vec {\beta }}} , and a vector ε → {\displaystyle {\vec
Polynomial_regression
Type of chart
(Box–Jenkins) Autoregressive conditional heteroskedasticity (ARCH) Vector autoregression (VAR) (Autoregressive model (AR)) Frequency domain Spectral density
Bar_chart
Statistical model for a binary dependent variable
follows: The regression coefficients β0, β1, ..., βm are grouped into a single vector β of size m + 1. For each data point i, an additional explanatory pseudo-variable
Logistic_regression
Type of numerical analysis
(Box–Jenkins) Autoregressive conditional heteroskedasticity (ARCH) Vector autoregression (VAR) (Autoregressive model (AR)) Frequency domain Spectral density
Isotonic_regression
Statistical model for count data
response. If x ∈ R n {\displaystyle \mathbf {x} \in \mathbb {R} ^{n}} is a vector of independent variables, then the model takes the form log ( E ( Y
Poisson_regression
Concept in statistical analysis
of causality known as Granger causality can be tested for, and vector autoregression can be performed to examine the intertemporal linkages between the
Bivariate_analysis
Concept in machine learning
(Box–Jenkins) Autoregressive conditional heteroskedasticity (ARCH) Vector autoregression (VAR) (Autoregressive model (AR)) Frequency domain Spectral density
Double_descent
Collection of statistical models
additional interaction term in the vector v k {\displaystyle v_{k}} and then add an intercept term. Let that vector be X k {\displaystyle X_{k}} . With
Analysis_of_variance
Estimator for quality of a statistical model
differences have been well-studied in regression variable selection and autoregression order selection problems. In general, if the goal is prediction, AIC
Akaike_information_criterion
Statistical test
{\displaystyle {\hat {\theta }}_{n}} is a P × 1 {\displaystyle P\times 1} vector), which is supposed to follow asymptotically a normal distribution with
Wald_test
Type of average of a collection of numbers
1 {\displaystyle 1} ), it can be defined on a convex space, not only a vector space. Statistician Churchill Eisenhart, senior researcher fellow at the
Arithmetic_mean
Task of selecting a statistical model from a set of candidate models
; Yang, Y. (June 2018). "Bridging AIC and BIC: A New Criterion for Autoregression". IEEE Transactions on Information Theory. 64 (6): 4024–4043. arXiv:1508
Model_selection
Diagnostic plot of binary classifier ability
(Box–Jenkins) Autoregressive conditional heteroskedasticity (ARCH) Vector autoregression (VAR) (Autoregressive model (AR)) Frequency domain Spectral density
Receiver operating characteristic
Receiver_operating_characteristic
Categorization of data using statistics
score to each possible category k by combining the feature vector of an instance with a vector of weights, using a dot product. The predicted category is
Statistical_classification
Frequency with which an engineered system or component fails
(Box–Jenkins) Autoregressive conditional heteroskedasticity (ARCH) Vector autoregression (VAR) (Autoregressive model (AR)) Frequency domain Spectral density
Failure_rate
Statistical measure of the magnitude of a phenomenon
(Box–Jenkins) Autoregressive conditional heteroskedasticity (ARCH) Vector autoregression (VAR) (Autoregressive model (AR)) Frequency domain Spectral density
Effect_size
Non-parametric method for testing whether samples originate from the same distribution
package HypothesisTests.jl has the function KruskalWallisTest(groups::AbstractVector{<:Real}...) to compute the p-value. One-way ANOVA Mann–Whitney U tests Bonferroni
Kruskal–Wallis_test
Processes that maintain quality at a constant level
(Box–Jenkins) Autoregressive conditional heteroskedasticity (ARCH) Vector autoregression (VAR) (Autoregressive model (AR)) Frequency domain Spectral density
Quality_control
Variable representing a random phenomenon
numbers. In this case, a random element may optionally be represented as a vector of real-valued random variables (all defined on the same underlying probability
Random_variable
Bayesian statistics Bayesian tool for methylation analysis Bayesian vector autoregression BCMP network – queueing theory Bean machine Behrens–Fisher distribution
List_of_statistics_articles
Data visualization
(Box–Jenkins) Autoregressive conditional heteroskedasticity (ARCH) Vector autoregression (VAR) (Autoregressive model (AR)) Frequency domain Spectral density
Box_plot
Value that appears most often in a set of data
any random variable assuming values from a vector space, including the real numbers (a one-dimensional vector space) and the integers (which can be considered
Mode_(statistics)
Type of statistics
(Box–Jenkins) Autoregressive conditional heteroskedasticity (ARCH) Vector autoregression (VAR) (Autoregressive model (AR)) Frequency domain Spectral density
Descriptive_statistics
Variable capable of taking on a limited number of possible values
real-valued (sometimes complex-valued) vector spaces, usually in such a way that ‘similar’ values are assigned ‘similar’ vectors, or with respect to some other
Categorical_variable
Statistical matching technique
( Z i = 0 {\displaystyle Z_{i}=0} ). Let X i {\displaystyle X_{i}} be a vector of observed pretreatment measurements (or covariates) for the ith subject
Propensity_score_matching
Statistical distribution for dependence between random variables
under the name permutons and doubly-stochastic measures. Consider a random vector ( X 1 , X 2 , … , X d ) . {\displaystyle \ {\bigl (}X_{1},X_{2},\dots
Copula_(statistics)
Statistical test
(Box–Jenkins) Autoregressive conditional heteroskedasticity (ARCH) Vector autoregression (VAR) (Autoregressive model (AR)) Frequency domain Spectral density
Z-test
Class of statistical models
multinomial distribution, and for the vector form of the categorical distribution, the expected values of the elements of the vector can be related to the predicted
Generalized_linear_model
Gathering information for analysis
(Box–Jenkins) Autoregressive conditional heteroskedasticity (ARCH) Vector autoregression (VAR) (Autoregressive model (AR)) Frequency domain Spectral density
Data_collection
Function of the observed sample results
(Box–Jenkins) Autoregressive conditional heteroskedasticity (ARCH) Vector autoregression (VAR) (Autoregressive model (AR)) Frequency domain Spectral density
P-value
Series of questions for gathering information
(Box–Jenkins) Autoregressive conditional heteroskedasticity (ARCH) Vector autoregression (VAR) (Autoregressive model (AR)) Frequency domain Spectral density
Questionnaire
Form of scientific experiment
(Box–Jenkins) Autoregressive conditional heteroskedasticity (ARCH) Vector autoregression (VAR) (Autoregressive model (AR)) Frequency domain Spectral density
Randomized_controlled_trial
Set of statistical processes for estimating the relationships among variables
as a scalar or vector β {\displaystyle \beta } . The independent variables, which are observed in data and are often denoted as a vector X i {\displaystyle
Regression_analysis
Criterion for model selection
S2CID 2884450. McQuarrie, A. D. R.; Tsai, C.-L. (1998). Regression and Time Series Model Selection. World Scientific. Sparse Vector Autoregressive Modeling
Bayesian information criterion
Bayesian_information_criterion
Statistical value representing the center or average of a distribution
data set X, thought of as a vector x = (x1,…,xn), the dispersion about a point c is the "distance" from x to the constant vector c = (c,…,c) in the p-norm
Central_tendency
Metric for fit of statistical models
(Box–Jenkins) Autoregressive conditional heteroskedasticity (ARCH) Vector autoregression (VAR) (Autoregressive model (AR)) Frequency domain Spectral density
Goodness_of_fit
(Box–Jenkins) Autoregressive conditional heteroskedasticity (ARCH) Vector autoregression (VAR) (Autoregressive model (AR)) Frequency domain Spectral density
List of probability distributions
List_of_probability_distributions
Sampling from a population which can be partitioned into subpopulations
(Box–Jenkins) Autoregressive conditional heteroskedasticity (ARCH) Vector autoregression (VAR) (Autoregressive model (AR)) Frequency domain Spectral density
Stratified_sampling
Probability distribution
(Box–Jenkins) Autoregressive conditional heteroskedasticity (ARCH) Vector autoregression (VAR) (Autoregressive model (AR)) Frequency domain Spectral density
Student's_t-distribution
Statistical property quantifying how much a collection of data is spread out
(Box–Jenkins) Autoregressive conditional heteroskedasticity (ARCH) Vector autoregression (VAR) (Autoregressive model (AR)) Frequency domain Spectral density
Statistical_dispersion
Mathematical relation assigning a probability event to a cost
a fixed but possibly unknown state of nature, X {\displaystyle X} is a vector of observations stochastically drawn from a population, E θ {\displaystyle
Loss_function
How many standard deviations apart from the mean an observed datum is
(Box–Jenkins) Autoregressive conditional heteroskedasticity (ARCH) Vector autoregression (VAR) (Autoregressive model (AR)) Frequency domain Spectral density
Standard_score
Statistical property of collections of time series data
integrated ( I ( 1 ) {\displaystyle I(1)} ) but some (cointegrating) vector of coefficients exists to form a stationary linear combination of them.
Cointegration
Representation of a type of random process
model is a special case of the vector autoregressive model, the computation of the impulse response in vector autoregression#impulse response applies here
Autoregressive_model
Method of statistical analysis
{\displaystyle y_{i}} given a k × 1 {\displaystyle k\times 1} predictor vector x i {\displaystyle \mathbf {x} _{i}} : y i = x i T β + ε i , {\displaystyle
Bayesian_linear_regression
Human research survey of public opinion
(Box–Jenkins) Autoregressive conditional heteroskedasticity (ARCH) Vector autoregression (VAR) (Autoregressive model (AR)) Frequency domain Spectral density
Opinion_poll
Statistical hypothesis test
(Box–Jenkins) Autoregressive conditional heteroskedasticity (ARCH) Vector autoregression (VAR) (Autoregressive model (AR)) Frequency domain Spectral density
Chi-squared_test
Mathematical function for the probability a given outcome occurs in an experiment
phenomenon being observed. The sample space may be any set of numbers, vectors, labels, or whatever else. For example, the sample space of a coin flip
Probability_distribution
Conditional probability used in Bayesian statistics
(Box–Jenkins) Autoregressive conditional heteroskedasticity (ARCH) Vector autoregression (VAR) (Autoregressive model (AR)) Frequency domain Spectral density
Posterior_probability
Signal representation
(Box–Jenkins) Autoregressive conditional heteroskedasticity (ARCH) Vector autoregression (VAR) (Autoregressive model (AR)) Frequency domain Spectral density
Frequency_domain
Table that displays the frequency of variables
(Box–Jenkins) Autoregressive conditional heteroskedasticity (ARCH) Vector autoregression (VAR) (Autoregressive model (AR)) Frequency domain Spectral density
Contingency_table
Method of statistical inference
technique is, however, equally applicable to discrete distributions. Let the vector θ {\displaystyle {\boldsymbol {\theta }}} span the parameter space. Let
Bayesian_inference
Statistical method for resampling
(Box–Jenkins) Autoregressive conditional heteroskedasticity (ARCH) Vector autoregression (VAR) (Autoregressive model (AR)) Frequency domain Spectral density
Jackknife_resampling
Statistical method
defined by a mean function and a covariance function, which specify the mean vectors and covariance matrices for each finite collection of the random variables
Bootstrapping_(statistics)
Statistical model validation technique
{\textstyle y_{1},\ldots ,y_{n}} , and n p-dimensional vector covariates x1, ..., xn. The components of the vector xi are denoted xi1, ..., xip. If least squares
Cross-validation_(statistics)
Test statistic
(Box–Jenkins) Autoregressive conditional heteroskedasticity (ARCH) Vector autoregression (VAR) (Autoregressive model (AR)) Frequency domain Spectral density
Durbin–Watson_statistic
Complete set of items that share at least one property in common
(Box–Jenkins) Autoregressive conditional heteroskedasticity (ARCH) Vector autoregression (VAR) (Autoregressive model (AR)) Frequency domain Spectral density
Statistical_population
Distribution function associated with the empirical measure of a sample
(Box–Jenkins) Autoregressive conditional heteroskedasticity (ARCH) Vector autoregression (VAR) (Autoregressive model (AR)) Frequency domain Spectral density
Empirical distribution function
Empirical_distribution_function
Type of chart
(Box–Jenkins) Autoregressive conditional heteroskedasticity (ARCH) Vector autoregression (VAR) (Autoregressive model (AR)) Frequency domain Spectral density
Radar_chart
Single measure of some attribute of a sample
(Box–Jenkins) Autoregressive conditional heteroskedasticity (ARCH) Vector autoregression (VAR) (Autoregressive model (AR)) Frequency domain Spectral density
Statistic
Regression analysis
{\displaystyle \mathbf {y} \sim f(\mathbf {x} ,{\boldsymbol {\beta }})} relates a vector of independent variables, x {\displaystyle \mathbf {x} } , and its associated
Nonlinear_regression
Statistic which divides a data set into 100 parts and analyzes it as a percentage
(Box–Jenkins) Autoregressive conditional heteroskedasticity (ARCH) Vector autoregression (VAR) (Autoregressive model (AR)) Frequency domain Spectral density
Percentile
Statistical method that summarizes and/or integrates data from multiple sources
(Box–Jenkins) Autoregressive conditional heteroskedasticity (ARCH) Vector autoregression (VAR) (Autoregressive model (AR)) Frequency domain Spectral density
Meta-analysis
Selection of data points in statistics
(Box–Jenkins) Autoregressive conditional heteroskedasticity (ARCH) Vector autoregression (VAR) (Autoregressive model (AR)) Frequency domain Spectral density
Sampling_(statistics)
Statistical test that compares goodness of fit
(Box–Jenkins) Autoregressive conditional heteroskedasticity (ARCH) Vector autoregression (VAR) (Autoregressive model (AR)) Frequency domain Spectral density
Likelihood-ratio_test
Middle quantile of a data set or probability distribution
median is defined for vectors defined with respect to a fixed set of coordinates. A marginal median is defined to be the vector whose components are univariate
Median
Study of collection and analysis of data
and estimation theory defines a random sample as the random vector given by the column vector of these IID variables. The population being examined is described
Statistics
Dividing things between two categories
classification are: Decision trees Random forests Bayesian networks Support vector machines Neural networks Logistic regression Probit model Genetic Programming
Binary_classification
Relationship between items in a set
(Box–Jenkins) Autoregressive conditional heteroskedasticity (ARCH) Vector autoregression (VAR) (Autoregressive model (AR)) Frequency domain Spectral density
Ranking
VECTOR AUTOREGRESSION
VECTOR AUTOREGRESSION
Male
Russian
(Cyrillic Виктор): Slavic form of Roman Latin Victor, VIKTOR means "conqueror." In use by the Bulgarians, Russians and Serbians. Compare with another form of Viktor.
Boy/Male
Christian & English(British/American/Australian)
Conqueror
Boy/Male
English American
Doctor; teacher.
Boy/Male
Spanish
Victor.
Male
Portuguese
Portuguese form of Latin Hector, HEITOR means "defend; hold fast."
Male
Portuguese
Galician-Portuguese form of Roman Latin Victor, VITOR means "conqueror."
Boy/Male
Latin American Spanish
Conqueror.
Boy/Male
Christian & English(British/American/Australian)
Steadfast
Male
Arthurian
, sir Hector de Maris; (defender).
Boy/Male
American, Australian, British, Chinese, Christian, Danish, Dutch, English, French, German, Greek, Italian, Latin, Portuguese, Shakespearean, Spanish
Steadfast; Anchor; Holds Fast; Star; Coined from Esther Vanhomrigh; Tenacious; Defend; Hold Fast; Coined from Esther Vanho
Male
Greek
(á¼ÎºÏ„ωÏ) Variant spelling of Greek Hektor, EKTOR means "defend; hold fast."
Boy/Male
Australian, Basque, Czech, Czechoslovakian, Danish, Finnish, French, German, Hungarian, Latin, Polish, Slovenia, Swedish, Swiss, Ukrainian
The Conqueror; Victory; Victorious; Conquer
Male
English
Short form of English Sylvester, VESTER means "from the forest."
Boy/Male
American, British, Christian, Danish, Dutch, English, Finnish, French, German, Greek, Hindu, Indian, Irish, Jamaican, Latin, Romanian, Slovenia, Spanish, Swedish, Swiss, Tamil, Ukrainian
Victorious; Conqueror; Winner; Champion; One who Conquers; Victory
Male
English
 Anglicized form of Scottish Gaelic Eachann, HECTOR means "brown horse." Compare with another form of Hector.
Boy/Male
Spanish American Shakespearean Greek Latin
Tenacious.
Boy/Male
Arthurian Legend
Father of Arthur.
Male
Scandinavian
 Scandinavian form of Roman Latin Victor, VIKTOR means "conqueror." Compare with another form of Viktor.
Surname or Lastname
Scottish
Scottish : Anglicized form of the Gaelic personal name Eachann (earlier Eachdonn, already confused with Norse Haakon), composed of the elements each ‘horse’ + donn ‘brown’.English : found in Yorkshire and Scotland, where it may derive directly from the medieval personal name. According to medieval legend, Britain derived its name from being founded by Brutus, a Trojan exile, and Hector was occasionally chosen as a personal name, as it was the name of the Trojan king’s eldest son. The classical Greek name, HektÅr, is probably an agent derivative of Greek ekhein ‘to hold back’, ‘hold in check’, hence ‘protector of the city’.German, French, and Dutch : from the personal name (see 2 above). In medieval Germany, this was a fairly popular personal name among the nobility, derived from classical literature. It is a comparatively rare surname in France.
Male
English
Roman Latin name VICTOR means "conqueror."Â
VECTOR AUTOREGRESSION
VECTOR AUTOREGRESSION
Boy/Male
Muslim/Islamic
Sword that the Prophet (S.A.W) gave to Sayyidina Ali
Girl/Female
Afghan, African, Arabic, Gujarati, Hebrew, Hindu, Indian, Kannada, Malayalam, Marathi, Muslim, Sindhi, Swahili, Tamil, Telugu
Good; Cheerful; Beautiful; Pretty
Boy/Male
Hindu, Indian
Lord Shiva
Boy/Male
Biblical, Christian, German, Hebrew
Voluntary; Praise Jehovah; Paternity; The Afflicted; Jehovah is Father; Whose Father is Jehovah
Male
English
Middle English form of Anglo-Saxon Cynebeal, KIMBEL means "royal courage."
Boy/Male
Tamil
Lord Kuber
Boy/Male
Muslim
Signal, Guidance, Guiding hand
Girl/Female
Arabic, Muslim
Deceptive
Girl/Female
Hindu
(Celebrity Name: Kumar Gaurav)
Surname or Lastname
English and Scottish
English and Scottish : variant of Strother.
VECTOR AUTOREGRESSION
VECTOR AUTOREGRESSION
VECTOR AUTOREGRESSION
VECTOR AUTOREGRESSION
VECTOR AUTOREGRESSION
n.
A term made up of the two parts / + /1 /-1, where / and /1 are vectors.
n.
An African weaver bird (Textor alector).
n.
Same as Radius vector.
n.
The turning factor of a quaternion.
v. t.
To tamper with and arrange for one's own purposes; to falsify; to adulterate; as, to doctor election returns; to doctor whisky.
n.
The ratio of one vector to another in length, no regard being had to the direction of the two vectors; -- so called because considered as a stretching factor in changing one vector into another. See Versor.
n.
The chief elective officer of some universities, as in France and Scotland; sometimes, the head of a college; as, the Rector of Exeter College, or of Lincoln College, at Oxford.
a.
Of or pertaining to victory, or a victor' being a victor; bringing or causing a victory; conquering; winning; triumphant; as, a victorious general; victorious troops; a victorious day.
n.
A woman who wins a victory; a female victor.
n.
A directed quantity, as a straight line, a force, or a velocity. Vectors are said to be equal when their directions are the same their magnitudes equal. Cf. Scalar.
n.
A pregnant woman; a mother; as, A has a son B by one venter, and a daughter C by another venter; children by different venters.
n.
The province of a rector; a parish church, parsonage, or spiritual living, with all its rights, tithes, and glebes.
v. t.
To treat as a physician does; to apply remedies to; to repair; as, to doctor a sick man or a broken cart.
a.
Pertaining to a rector or a rectory; rectoral.
n.
A mathematical instrument, consisting of two rulers connected at one end by a joint, each arm marked with several scales, as of equal parts, chords, sines, tangents, etc., one scale of each kind on each arm, and all on lines radiating from the common center of motion. The sector is used for plotting, etc., to any scale.
v. t.
To confer a doctorate upon; to make a doctor.
n.
A contrivance for removing superfluous ink or coloring matter from a roller. See Doctor, 4.
n.
A belly, or protuberant part; a broad surface; as, the venter of a muscle; the venter, or anterior surface, of the scapula.
n.
Any mechanical contrivance intended to remedy a difficulty or serve some purpose in an exigency; as, the doctor of a calico-printing machine, which is a knife to remove superfluous coloring matter; the doctor, or auxiliary engine, called also donkey engine.
n.
An astronomical instrument, the limb of which embraces a small portion only of a circle, used for measuring differences of declination too great for the compass of a micrometer. When it is used for measuring zenith distances of stars, it is called a zenith sector.