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Technique used in statistics
Log-linear analysis is a technique used in statistics to examine the relationship between more than two categorical variables. The technique is used for
Log-linear_analysis
Mathematical model
A log-linear model is a mathematical model that takes the form of a function whose logarithm equals a linear combination of the parameters of the model
Log-linear_model
Statistical modeling method
median or some other quantile is used. Like all forms of regression analysis, linear regression focuses on the conditional probability distribution of the
Linear_regression
Method used in statistics, pattern recognition, and other fields
Linear discriminant analysis (LDA), normal discriminant analysis (NDA), canonical variates analysis (CVA), or discriminant function analysis is a generalization
Linear_discriminant_analysis
2D graphic with logarithmic scales on both axes
k log x + log a . {\displaystyle \log y=k\log x+\log a.} Setting X = log x {\displaystyle X=\log x} and Y = log y , {\displaystyle Y=\log y,}
Log–log_plot
Set of statistical processes for estimating the relationships among variables
The most common form of regression analysis is linear regression, in which one finds the line (or a more complex linear combination) that most closely fits
Regression_analysis
Class of statistical models
log(μ) be a linear model. This produces the "cloglog" transformation log ( − log ( 1 − p ) ) = log ( μ ) . {\displaystyle \log(-\log(1-p))=\log(\mu
Generalized_linear_model
Statistical model for a binary dependent variable
model that models the log-odds of an event as a linear combination of one or more independent variables. In regression analysis, logistic regression (or
Logistic_regression
Set of random variables
theorem Hopfield network Interacting particle system Ising model Log-linear analysis Markov chain Markov logic network Maximum entropy method Stochastic
Markov_random_field
Method of data analysis
Principal component analysis (PCA) is a linear dimensionality reduction technique with applications in exploratory data analysis, visualization and data
Principal_component_analysis
Transforming data by taking the logarithm
Another reason for applying the log data transformation is to improve interpretability, even if no formal statistical analysis or visualization is to be performed
Log transformation (statistics)
Log_transformation_(statistics)
Statistical model for count data
In statistics, Poisson regression is a generalized linear model form of regression analysis used to model count data and contingency tables. Poisson regression
Poisson_regression
Branch of statistics
extended to survival estimation. The DeepSurv model proposes to replace the log-linear parameterization of the CoxPH model with a multi-layer perceptron. Further
Survival_analysis
Study of resources used by an algorithm
slowly: (binary) iterated logarithm (log*) is less than 5 for all practical data (265536 bits); (binary) log-log (log log n) is less than 6 for virtually all
Analysis_of_algorithms
Statistical linear model
The general linear model or general multivariate regression model is a compact way of simultaneously writing several multiple linear regression models
General_linear_model
Linear regression model with a single explanatory variable
In statistics, simple linear regression (SLR) is a linear regression model with a single explanatory variable. That is, it concerns two-dimensional sample
Simple_linear_regression
Theory in crisis communication
effect, and "a large number of cases could be coded and subjected to log-linear analysis to identify patterns." (Coombs, 2006, p. 191-192) Coca-Cola and Pepsi's
Image_restoration_theory
Approximate distinct counting algorithm
standard HyperLogLog estimator E {\textstyle E} above. Otherwise, use Linear Counting: E ⋆ = m log ( m V ) {\textstyle E^{\star }=m\log \left({\frac
HyperLogLog
results. Common methods include Linear Analysis, Semi-log Analysis and Log-Log Analysis The Linear Method is the analysis of the function N(r), where N
Sholl_analysis
Collection of statistical models
Explained variation Linear trend estimation Mixed-design analysis of variance Multivariate analysis of covariance (MANCOVA) Permutational analysis of variance
Analysis_of_variance
Species of reptile
(A. veronensis has relatively more robust head). Differences in log-linear analysis of both lizard's colouration were negligible, the same goes for insufficient
Anguis_veronensis
Probabilistic graphical representation of causal relationships
pp. 1855–1863. Petitjean F, Webb GI, Nicholson AE (2013). Scaling log-linear analysis to high-dimensional data (PDF). International Conference on Data
Bayesian_network
Smooth approximation to the maximum function
in log probability. Similar to multiplication operations in linear-scale becoming simple additions in log-scale, an addition operation in linear-scale
LogSumExp
Local regression Log-Cauchy distribution Log-Laplace distribution Log-normal distribution Log-linear analysis Log-linear model Log-linear modeling – redirects
List_of_statistics_articles
Statistical method
Factor analysis searches for such joint variations in response to unobserved latent variables. The observed variables are modelled as linear combinations
Factor_analysis
Class of statistical survival models
Laird and Donald Olivier (1981). "Covariance Analysis of Censored Survival Data Using Log-Linear Analysis Techniques". Journal of the American Statistical
Proportional_hazards_model
Approximation method in statistics
state that the least-squares approach to regression analysis is optimal in the sense that in a linear model where the errors have a mean of zero, are uncorrelated
Least_squares
Measure of the joint variability
random variables. The sign of the covariance shows the tendency in the linear relationship between the variables. Covariance is positive when variables
Covariance
Estimate of time taken for running an algorithm
quasilinear time (also referred to as log-linear time) if T ( n ) = O ( n log k n ) {\displaystyle T(n)=O(n\log ^{k}n)} for some positive constant k;
Time_complexity
Method of statistical analysis
Bayesian linear regression is a type of conditional modeling in which the mean of one variable is described by a linear combination of other variables
Bayesian_linear_regression
Function in statistics
(logistic unit) or log-odds function is the quantile function associated with the standard logistic distribution. It has many uses in data analysis and machine
Logit
Task of selecting a statistical model from a set of candidate models
Feature selection Freedman's paradox Grid search Identifiability Analysis Log-linear analysis Model identification Occam's razor Optimal design Parameter identification
Model_selection
Type of activation function
context of artificial neural networks, the rectifier or ReLU (rectified linear unit) activation function is an activation function defined as the non-negative
Rectified_linear_unit
American public health researcher
study of the relative efficiency of regression analysis, discriminant analysis, and log linear analysis in predicting the future enrollment status of educational
Robert_Fullilove
General linear model that blends ANOVA and regression
Analysis of covariance (ANCOVA) is a general linear model that blends ANOVA and regression. ANCOVA evaluates whether the means of a dependent variable
Analysis_of_covariance
Generates a forecast of future values of a time series
estimates of the linear trend. The use of the exponential window function is first attributed to Poisson as an extension of a numerical analysis technique from
Exponential_smoothing
Function related to statistics and probability theory
with: log L ( α , β ∣ x ) = α log β − log Γ ( α ) + ( α − 1 ) log x − β x . {\displaystyle \log {\mathcal {L}}(\alpha ,\beta \mid x)=\alpha \log \beta
Likelihood_function
Least squares approximation of linear functions to data
Linear least squares (LLS) is the least squares approximation of linear functions to data. It is a set of formulations for solving statistical problems
Linear_least_squares
Method to detect power-law scaling in time series
the log-log plot of log n − log F q ( n ) {\displaystyle \log n-\log F_{q}(n)} , If there is a strong linearity in the plot of log n − log F q
Detrended fluctuation analysis
Detrended_fluctuation_analysis
Sequence of data points over time
any particular structure. Methods of time series analysis may also be divided into linear and non-linear, and univariate and multivariate. A time series
Time_series
Mathematical function, inverse of an exponential function
formula: log b x = log 10 x log 10 b = log e x log e b . {\displaystyle \log _{b}x={\frac {\log _{10}x}{\log _{10}b}}={\frac {\log _{e}x}{\log _{e}b}}
Logarithm
Parametric model in survival analysis
accelerated failure time model to regression analysis (typically a linear model) where − log ( θ ) {\displaystyle -\log(\theta )} represents the fixed effects
Accelerated failure time model
Accelerated_failure_time_model
Diagnostic plot of binary classifier ability
can be generalized to multiple classes) at varying threshold values. ROC analysis is commonly applied in the assessment of diagnostic test performance in
Receiver operating characteristic
Receiver_operating_characteristic
Approximation method in statistics
Non-linear least squares is the form of least squares analysis used to fit a set of m observations with a model that is non-linear in n unknown parameters
Non-linear_least_squares
Multidisciplinary academic field that focuses on leadership in organizational contexts
leadership (e.g., cross-tabulations, ANOVAs, regression analysis, log-linear analysis, factor analysis, etc.). From a qualitative orientation, leadership research
Leadership_studies
Generalization of the one-dimensional normal distribution to higher dimensions
normalization constant. A similar notation is used for multiple linear regression. Since the log likelihood of a normal vector is a quadratic form of the normal
Multivariate normal distribution
Multivariate_normal_distribution
Statistical model validation technique
model validation techniques for assessing how the results of a statistical analysis will generalize to an independent data set. Cross-validation includes resampling
Cross-validation_(statistics)
Data structure for storing non-overlapping sets
"Top-down analysis of path compression", SIAM J. Comput. 34(3):515–525, 2005 Tarjan, Robert Endre (1975). "Efficiency of a Good But Not Linear Set Union
Disjoint-set_data_structure
Family of functions to transform data
normal log likelihood at its maximum to be written as follows: log ( L ( μ ^ , σ ^ ) ) = ( − n / 2 ) ( log ( 2 π σ ^ 2 ) + 1 ) + n ( λ − 1 ) log (
Power_transform
Statistical method that summarizes and/or integrates data from multiple sources
using Bayesian methods, mixed linear models and meta-regression approaches. Specifying a Bayesian network meta-analysis model involves writing a directed
Meta-analysis
Simultaneous observation and analysis of more than one outcome variable
quantities are of interest to the same analysis. Certain types of problems involving multivariate data, for example simple linear regression and multiple regression
Multivariate_statistics
Nonparametric measure of rank correlation
Pearson's correlation assesses linear relationships, Spearman's correlation assesses monotonic relationships (whether linear or not). If there are no repeated
Spearman's rank correlation coefficient
Spearman's_rank_correlation_coefficient
Numerical measure of a statistical relationship between variables
correlation coefficient is a numerical measure of some type of linear correlation, meaning a linear function between two variables. The variables may be two
Correlation_coefficient
Fourth standardized moment in statistics
)^{4}\right].} Assume we sample n = 2 3 + 3 3 κ log 1 δ {\displaystyle n={\tfrac {2{\sqrt {3}}+3}{3}}\kappa \log {\tfrac {1}{\delta }}} many independent copies
Kurtosis
Inverse of the average of the inverses of a set of numbers
{\displaystyle m={\frac {1}{n}}\sum \log _{e}(x)} s 2 = 1 n ∑ ( log e ( x ) − m ) 2 {\displaystyle s^{2}={\frac {1}{n}}\sum \left(\log _{e}(x)-m\right)^{2}} Of
Harmonic_mean
Concept in statistical analysis
simple linear regression). Bivariate analysis can be contrasted with univariate analysis in which only one variable is analysed. Like univariate analysis, bivariate
Bivariate_analysis
Measure of linear correlation
unqualified correlation coefficient, is a correlation coefficient that measures linear correlation between two sets of data. It is the ratio between the covariance
Pearson correlation coefficient
Pearson_correlation_coefficient
Characteristic of a chemical reaction
(REFER). Using REFER, a linear free energy relationship can be written as log k = α log K + β {\displaystyle \log k=\alpha \log K+\beta } or relative
Free-energy_relationship
Experimental design in statistics
Application of the Linear Model. Pacific Grove, CA: Wadsworth & Brooks/Cole. ISBN 0-87872-108-8. Hocking, Ronald R. (1985). The Analysis of Linear Models. Pacific
Factorial_experiment
Concept in probability theory and statistics
other); the value 1 conveys a perfect positive linear relationship, and the value 0 conveys that there is no linear relationship. The partial correlation coincides
Partial_correlation
Correlation of a signal with a time-shifted copy of itself, as a function of shift
variance of a linear combination of the X {\displaystyle X} 's, the variance calculated may turn out to be negative. In time series analysis, the Hassani
Autocorrelation
Statistical model containing both fixed effects and random effects
mixed-effects model Fixed effects model Generalized linear mixed model Linear regression Mixed-design analysis of variance Multilevel model Random effects model
Mixed_model
Periodicity computation method
Least-squares spectral analysis (LSSA) is a class of methods for estimating a frequency spectrum by fitting sinusoids to data using a least-squares fit
Least-squares spectral analysis
Least-squares_spectral_analysis
Branch of statistics
are commonly used in statistics include mathematical analysis, linear algebra, stochastic analysis, differential equations, and measure theory. Statistical
Mathematical_statistics
Measure of goodness of fit for a statistical model
deviance used in the context of generalized linear modelling, − 2 log [ p ( y ∣ θ ^ 0 ) ] {\displaystyle -2\log {\big [}p(y\mid {\hat {\theta }}_{0}){\big
Deviance_(statistics)
Specialized form of regression analysis, in statistics
1037/0003-066X.34.7.571. archived pdf Draper, David (1988). "Rank-Based Robust Analysis of Linear Models. I. Exposition and Review". Statistical Science. 3 (2): 239–257
Robust_regression
Regression for more than two discrete outcomes
basic setup (the perceptron algorithm, support vector machines, linear discriminant analysis, etc.) is the procedure for determining (training) the optimal
Multinomial logistic regression
Multinomial_logistic_regression
Mathematical relation assigning a probability event to a cost
applied using linear regression theory, which is based on the quadratic loss function. The quadratic loss function is also used in linear-quadratic optimal
Loss_function
N-th root of the product of n numbers
( log 2 1 + log 2 2 + log 2 8 + log 2 16 ) / 4 = 2 ( 0 + 1 + 3 + 4 ) / 4 = 2 2 = 4. {\displaystyle {\sqrt[{4}]{1\cdot 2\cdot 8\cdot 16}}=2^{(\log _{2}\
Geometric_mean
Statistical test that compares goodness of fit
likelihood-ratio test statistic is expressed as a difference between the log-likelihoods λ LR = − 2 [ ℓ ( θ 0 ) − ℓ ( θ ^ ) ] {\displaystyle \lambda
Likelihood-ratio_test
Number of values in the final calculation of a statistic that are free to vary
the context of linear models (linear regression, analysis of variance), where certain random vectors are constrained to lie in linear subspaces, and the
Degrees of freedom (statistics)
Degrees_of_freedom_(statistics)
Statistics concept
as a statistical estimation problem it is linear, in the sense that the regression function E(y | x) is linear in the unknown parameters that are estimated
Polynomial_regression
Probability distribution
of a log-normal data set?, URL (version: 2022-12-18): https://stats.stackexchange.com/q/33395 Land, C. E. (1971), "Confidence intervals for linear functions
Log-normal_distribution
Type of stochastic process
Spectral Analysis and Time Series. Academic Press. ISBN 0-12-564922-3. Priestley, M. B. (1988). Non-linear and Non-stationary Time Series Analysis. Academic
Stationary_process
Continuous probability distribution for a non-negative random variable
but not β {\displaystyle \beta } by modelling it log ( α ) {\displaystyle \log(\alpha )} as a linear function of the covariates. The survival function
Log-logistic_distribution
Table that displays the frequency of variables
Discrete Multivariate Analysis: Theory and Practice. MIT Press. ISBN 978-0-262-02113-5. MR 0381130. Christensen, Ronald (1997). Log-linear models and logistic
Contingency_table
Value that appears most often in a set of data
concept of median does not apply. The median makes sense when there is a linear order on the possible values. Generalizations of the concept of median to
Mode_(statistics)
Concept in statistics
class of vector generalized linear models (VGLMs) was proposed to enlarge the scope of models catered for by generalized linear models (GLMs). In particular
Vector generalized linear model
Vector_generalized_linear_model
Measure of covariance of components of a random vector
\mathbb {R} ^{n}} Proof Indeed, from the property 4 it follows that under linear transformation of random variable X {\displaystyle \mathbf {X} } with covariation
Covariance_matrix
Fundamental theorem in probability theory and statistics
number of edges, and in fact, faces of all dimensions. A linear function of a matrix M is a linear combination of its elements (with given coefficients)
Central_limit_theorem
Kth smallest value in a statistical sample
I(U_{(r)};U_{(m)})=T_{m-1}+T_{n-r}-T_{m-r+1}-T_{n}} where T k = log ( k ! ) − k H k {\displaystyle T_{k}=\log(k!)-kH_{k}} where H k {\displaystyle H_{k}} is the
Order_statistic
Distinction between nominal, ordinal, interval and ratio variables
in educational contexts often indicate that total scores have a fairly linear relationship with measurements across the range of an assessment. Thus,
Level_of_measurement
In numerical analysis, nested dissection is a divide and conquer heuristic for the solution of sparse symmetric systems of linear equations based on graph
Nested_dissection
Estimator for quality of a statistical model
density function for the log-normal distribution. We then compare the AIC value of the normal model against the AIC value of the log-normal model. For misspecified
Akaike_information_criterion
Distribution of an uncertain quantity
log [ p ( x ∣ t ) ] d x d t − ∫ p ( x ) log [ p ( x ) ] d x {\displaystyle KL=\int p(t)\int p(x\mid t)\log[p(x\mid t)]\,dx\,dt\,-\,\int p(x)\log[p(x)]\
Prior_probability
Matrix programming language
toolboxes are available for GAUSS at additional cost. List of numerical-analysis software Burschka, Martin A.; Ehud Kalpan; Keith Purpura; Clay Reid; Ellen
GAUSS_(software)
Way of inferring information from cross-covariance matrices
correlations among the variables, then canonical-correlation analysis will find linear combinations of X and Y that have a maximum correlation with each
Canonical_correlation
Statistical relationship
data. It usually refers to the extent to which a pair of quantities are linearly related. More generally, an arbitrary relationship between variables is
Correlation
Grouping a set of objects by similarity
number of clusters in a data set Parallel coordinates Structured data analysis Linear separability Driver and Kroeber (1932). "Quantitative Expression of
Cluster_analysis
Statistical hypothesis test for forecasting
for latent confounding effects and does not capture instantaneous and non-linear causal relationships, though several extensions have been proposed to address
Granger_causality
Type of Monte Carlo algorithms for signal processing and statistical inference
Chain Monte Carlo techniques, conventional linearization, extended Kalman filters, or determining the best linear system (in the expected cost-error sense)
Particle_filter
parameterized with data using linear least squares, and subsumes the log-logistic distribution as a special case. The log-normal distribution, describing
List of probability distributions
List_of_probability_distributions
Speech analysis and encoding technique
information of a linear predictive model. LPC is the most widely used method in speech coding and speech synthesis. It is a powerful speech analysis technique
Linear_predictive_coding
Statistics model
distribution, the complementary log-log model. Linear approximation Cox, D. R. (1970). "Simple Regression". Analysis of Binary Data. London: Methuen.
Linear_probability_model
Form of causal modeling that fit networks of constructs to data
the concerns motivating economic models. Judea Pearl extended SEM from linear to nonparametric models, and proposed causal and counterfactual interpretations
Structural_equation_modeling
Measure of statistical dispersion
data set is divided into quartiles, or four rank-ordered even parts via linear interpolation. These quartiles are denoted by Q1 (also called the lower
Interquartile_range
Method of estimating the parameters of a statistical model, given observations
Strategies for Analysis. Cambridge University Press. ISBN 978-1-316-63682-4. Tilevik, Andreas (2022). Maximum likelihood vs least squares in linear regression
Maximum_likelihood_estimation
Application of a function to each point in a data set
ratio of 1 corresponds to equality. In an analysis where X and Y are treated symmetrically, the log-ratio log(X / Y) is zero in the case of equality, and
Data transformation (statistics)
Data_transformation_(statistics)
Statistic for rank correlation
algorithm can be used to compute the numerator in O ( n ⋅ log n ) {\displaystyle O(n\cdot \log {n})} time. Begin by ordering your data points sorting by
Kendall rank correlation coefficient
Kendall_rank_correlation_coefficient
How many standard deviations apart from the mean an observed datum is
Multivariate Analysis (Fifth ed.), Chapman & Hall/CRC, ISBN 978-1439816806 Kutner, Michael; Nachtsheim, Christopher; Neter, John (204), Applied Linear Regression
Standard_score
LOG LINEAR-ANALYSIS
LOG LINEAR-ANALYSIS
Boy/Male
Hindu
Lingam
Surname or Lastname
English and French
English and French : nickname for a tall person, from Old English lang, long, Old French long ‘long’, ‘tall’ (equivalent to Latin longus).Irish (Ulster (Armagh) and Munster) : reduced Anglicized form of Gaelic Ó Longáin (see Langan).Chinese : from the name of an official treasurer called Long, who lived during the reign of the model emperor Shun (2257–2205 bc). his descendants adopted this name as their surname. Additionally, a branch of the Liu clan (see Lau 1), descendants of Liu Lei, who supposedly had the ability to handle dragons, was granted the name Yu-Long (meaning roughly ‘resistor of dragons’) by the Xia emperor Kong Jia (1879–1849 bc). Some descendants later simplified Yu-Long to Long and adopted it as their surname.Chinese : there are two sources for this name. One was a place in the state of Lu in Shandong province during the Spring and Autumn period (722–481 bc). The other source is the Xiongnu nationality, a non-Han Chinese people.Chinese : variant of Lang.Cambodian : unexplained.
Biblical
the multitude of Gog
Female
English
Variant spelling of English Linsey, LINSAY means "Lincoln's wetlands."
Female
Scottish
Variant spelling of Scottish Lilias, LILEAS means "lily."
Boy/Male
French, German, Polish
Long
Surname or Lastname
English
English : variant of Lingard.French : occupational name for a maker of or dealer in linen goods, from Old French linge ‘linen (goods)’ (see Linge 1).
Male
Scandinavian
Scandinavian form of Old Norse Einarr, EINAR means "lone warrior."
Male
Greek
(ΑἰνÎας) Variant spelling of Greek AineÃas, AINEAS means "praiseworthy."
Male
English
 English short form of Spanish Alonso, LON means "noble and ready." Compare with another form of Lon.
Male
French
 French form of Latin Eligius, ÉLOY means "to choose."
Male
Greek
(Λώτ) Greek form of Hebrew Lowt, LOT means "covering, veil." In the bible, this is the name of a nephew of Abraham and father of Moab.
Male
English
Irish Anglicized form of Gaelic Fionnbarr, FINBAR means "fair-headed."
Male
English
English unisex short form of French Louis and Louise, both LOU means "famous warrior."Â
Male
French
French form of Latin Eligius, ÉLOI means "to choose."
Male
Yiddish
 Variant spelling of Yiddish Lieber, LIBER means "beloved." Compare with another form of Liber.
Surname or Lastname
English
English : habitational name from Lingart, Lancashire, or Lingards Wood in Marsden, West Yorkshire, both named from Old English līn ‘flax’ + garðr ‘enclosure’.
Surname or Lastname
English
English : metronymic from Line.
Female
Spanish
Spanish form of Greek Lois, possibly LOÃDA means "agreeable."
Girl/Female
Biblical
The multitude of Gog.
LOG LINEAR-ANALYSIS
LOG LINEAR-ANALYSIS
Boy/Male
Muslim
Support, Prop
Boy/Male
British, English
Son of the Slayer
Boy/Male
Arabic, Muslim
Rich; Leader
Girl/Female
Muslim/Islamic
Confidential talk secret conversation
Boy/Male
Sikh
Brave God
Boy/Male
American, Australian, Bengali, Biblical, British, Chinese, Christian, Czechoslovakian, Danish, Dutch, English, Finnish, French, German, Greek, Hebrew, Indian, Irish, Jamaican, Latin, Lebanese, Netherlands, Portuguese, Shakespearean, Slovenia, Swedish, Swi
Rock; Stone; River; Strong
Male
Greek
(ΣÎÏγιος) Greek form of Latin Sergius, possibly SERGIOS means "sergeant."
Girl/Female
Tamil
Sriksha | à®·à¯à®°à¯€à®•à¯à®·
Girl/Female
Hindu, Indian
Goddess Laxmi
Girl/Female
Tamil
Sumadeepika | ஸà¯à®®à®¾à®‚திபீகா
Glittering flower
LOG LINEAR-ANALYSIS
LOG LINEAR-ANALYSIS
LOG LINEAR-ANALYSIS
LOG LINEAR-ANALYSIS
LOG LINEAR-ANALYSIS
n.
A part of the log. See Log-chip, and 2d Log, n., 2.
adv.
In a linear manner; with lines.
adv.
In a low position or manner; not aloft; not on high; near the ground.
a.
In the direction of a line; of or pertaining to a line; measured on, or ascertained by, a line; linear; as, lineal magnitude.
n.
One who adjusts things to a line or lines or brings them into line.
a.
Like a line; narrow; of the same breadth throughout, except at the extremities; as, a linear leaf.
v. t.
To enter in a ship's log book; as, to log the miles run.
a.
Of, pertaining to, or included by, two lines; as, bilinear coordinates.
a.
Last; long-delayed; -- obsolete, except in the phrase lag end.
a.
Of or pertaining to a line; consisting of lines; in a straight direction; lineal.
v. i.
To engage in the business of cutting or transporting logs for timber; to get out logs.
a.
Composed of lines; delineated; as, lineal designs.
n.
Hence: The record of the rate of ship's speed or of her daily progress; also, the full nautical record of a ship's cruise or voyage; a log slate; a log book.
a.
Of a linear shape.
v. t.
To mark with a line or lines; to cover with lines; as, to line a copy book.
a.
Linear.
a.
Descending in a direct line from an ancestor; hereditary; derived from ancestors; -- opposed to collateral; as, a lineal descent or a lineal descendant.
adv.
To a great extent in apace; as, a long drawn out line.
n.
One who lines, as, a liner of shoes.
n.
A thin, flat piece of board in the form of a quadrant of a circle attached to the log line; -- called also log-ship. See 2d Log, n., 2.