1 ) such that tf.reduce_sum(probs, -1) = 1 , and a total_count number of trials, i.e., the number of trials per draw from the Multinomial. in R. Please help. tfd_multivariate_student_t_linear_operator(), tfd_student_t_process(), tfd_multivariate_normal_diag(), The Kumaraswamy distribution is defined over the (0, 1) interval using parameters concentration1 (aka "alpha") and concentration0 (aka "beta"). tfd_deterministic(), logical; if TRUE (default), probabilities are \(P[X \le x]\) In this paper, a new distribution, generalized inverted Kumaraswamy (GIKum) distribution is introduced. tfd_quantized(), $$, Quantile function tfd_poisson(), Shape of Distribution Basic Properties tfd_gaussian_process_regression_model(), F(x) = 1-(1-x^a)^b Package index. tfd_logistic(), tfd_zipf(), Multi-level modeling with Hamiltonian Monte Carlo, Uncertainty estimates with layer_dense_variational, tfd_joint_distribution_named_auto_batched, tfd_joint_distribution_sequential_auto_batched, tfd_multivariate_normal_diag_plus_low_rank, tfd_multivariate_student_t_linear_operator, tfd_poisson_log_normal_quadrature_compound. Implies self$dtype and tfd_pareto(), tfd_vector_laplace_linear_operator(), Density, distribution function, quantile function and random generation for the Kumaraswamy distribution. 2. has a kumaraswamy odd Rayleigh-Log-Logistic distribution i.e. By using the LKD and the T-X distribution by Alzaatreh et al. tfd_pixel_cnn(), $$. tfd_geometric(), name prefixed to Ops created by this class. In probability and statistics, the Kumaraswamy's double bounded distribution is a family of continuous probability distributions defined on the interval (0,1). Kumaraswamy distribution. where N < r > has the Sibuya distribution (7) with parameter α = < r > and is independent of the IID {X j} with the CDF F. When we set r = β and apply the first representation in (14) to a Kumaraswamy random variable T~K α, β, , we obtain f(x) = abx^{a-1} (1-x^a)^{b-1} 82 I. tfd_half_cauchy(), The probability density function (pdf) is. tfd_transformed_distribution(), rdrr.io Find an R package R language docs Run R in your browser R Notebooks. Default value: FALSE. [8] is given by Fx Gx( ) =1 (1 ( ( )) ) ,−− ab (1) Where a>0, b>0 are shape parameters and G is the cdf of a continuous random variable . “Estimation of reservoir yield and storage distribution using moments analysis”. tfd_linear_gaussian_state_space_model(), The truncnorm package provides d, p, q, r functions for the truncated gaussian distribution as well as functions for the first two moments. tfd_cholesky_lkj(), Although some studies have been conducted for the Lindley distribution, the Kumaraswamy distribution is not very common among statisticians and has been little explored in the literature. extraDistr Additional Univariate and Multivariate Distributions. Cordeiro, G.M. tfd_von_mises_fisher(), self$batch_shape, i.e., tfd_batch_reshape(), (2013). tfd_sample(), tfd_log_prob(), tfd_mean(). Journal of Data Science 10(2012), 195-224 The Kumaraswamy Generalized Half-Normal Distribution for Skewed Positive Data Gauss M. Cordeiro1, Rodrigo R. Pescim2 and Edwin M. M. Ortega2 1UFPE and 2 ESALQ - USP Abstract: For the rst time, we propose and study the Kumaraswamy gen- Logical, default FALSE. Density, distribution function, quantile function and random generation tfd_beta_binomial(), The Kumaraswamy distribution on the interval (0,1), has its probability density function (pdf) with two shape parameters a … tfd_laplace(), tfd_triangular(), We propose a new four parameters continuous model called the Topp Leone generalized inverted Kumaraswamy distribution which extends the generalized inverted Kumaraswamy distribution. tfd_multinomial(), Positive floating-point Tensor indicating mean tfd_hidden_markov_model(), and Jones by replacing the baseline distribution with the Kumaraswamy (Kw) distribution to construct a new class of Kw-G distributions A closely related generalized distribution similar to using the beta random variable as the baseline distribution as defined in Eqs. When FALSE invalid inputs may tfd_vector_diffeomixture(), tfd_chi(), tfd_joint_distribution_named_auto_batched(), tfd_gamma_gamma(), tfd_chi2(), The Kumaraswamy tfd_von_mises(), However, it is a special case of the log-exponentiated Kumaraswamy distribution stud-ied by Lemonte et al. one or more of the statistic's batch members are undefined. tfd_gamma(), The Kumaraswamy (2,q) distribution is that of the” generating variate 2 2 { } R x x x x= +1 2 1 2when , Follow a bivariate Pearson Type II distribution [K.T. The paper by Kumaraswamy proposed a two-parameter distribution on (0,1), so-called Kumaraswamy distribution. Kumaraswamy distribution Source: R/distributions.R. When TRUE, statistics (e.g., mean, mode, variance) It has a shape similar to the Beta distribution, but is easier to reparameterize. tfd_cauchy(), Gaussian (or normal) distribution and its extensions: Base R provides the d, p, q, r functions for this distribution (see above).actuar provides the moment generating function and moments. tfd_variational_gaussian_process(), This has been used in an algorithm to generate univariate symmetric beta random variates [31] , [4] . tfd_power_spherical(), tfd_relaxed_bernoulli(), tfd_multivariate_normal_linear_operator(), pkumar(q, a = 1, b = 1, lower.tail = TRUE, log.p = FALSE), qkumar(p, a = 1, b = 1, lower.tail = TRUE, log.p = FALSE). tfd_vector_laplace_diag(), tfd_relaxed_one_hot_categorical(), tfd_normal(), tfd_poisson_log_normal_quadrature_compound(), x ~ K O R L L ( α , λ , δ , τ ) . tfd_continuous_bernoulli(), It has a A further special case of the Kumaraswamy distribution has also appeared elsewhere. tfd_wishart_linear_operator(), the length is taken to be the number required. $$ tfd_sinh_arcsinh(), Kumaraswamy distribution Where do you meet this distribution? The techniques to find appropriate new models for data sets are very popular nowadays among the researchers of this area where existed models in the literature are not suitable. It is similar to the Beta distribution, but much simpler to use especially in simulation studies since its probability density function, cum tfd_half_normal(), tfd_binomial(), tfd_kumaraswamy.Rd. Hydrology. Fletcher, S.G., and Ponnambalam, K. (1996). r n a l o f B i o m e tri c s & B i o s t a t i s t i c s ISSN: 211 Keywords: Newton-Raphson, Kumaraswamy distribution, Uniantimodal, Probability Introduction Kumaraswamy [1] introduced a two parameter absolutely continuous distribution which compares extremely favorably, in terms of simplicity, with the beta distribution. tfd_mixture(), Otherwise has same semantics as tfd_dirichlet_multinomial(), tfd_multivariate_normal_full_covariance(), tfd_student_t(), otherwise, \(P[X > x]\). tfd_dirichlet(), Description Usage Arguments Value Author(s) References See Also Examples. tfd_autoregressive(), tfd_inverse_gamma(), tfd_categorical(), Logical, default TRUE. Several distributional properties of the distribution are discussed in this chapter, which includes limiting behavior, mode, quantiles, moments, skewness, kurtosis, Shannon’s entropy, and order statistics. concentration1. In this chapter, a new generalization of the Kumaraswamy distribution, namely the gamma-Kumaraswamy distribution is defined and studied. and de Castro, M. (2009). and (), is the work due to Cordeiro and de Castro (), where the authors combined the works of Eugene et al. tfd_horseshoe(), concentration0 = beta, The Kum cumulative distribution function (cdf) is defined by (1) G Kum ( x ; α , β ) = 1 − ( 1 − x α ) β , x ∈ ( 0 , 1 ) , where α > 0 and β > 0 are shape parameters. Positive floating-point Tensor indicating mean In lmomco: L-Moments, Censored L-Moments, Trimmed L-Moments, L-Comoments, and Many Distributions. tfd_vector_exponential_diag(), logical; if TRUE, probabilities p are given as log(p). tfd_vector_exponential_linear_operator(), tfd_wishart(), The KR Distribution The Kumaraswamy-Generalized distribution The cumulative density function (cdf) of the Kumaraswamy-Generalized (Kum-Generalized) distribution proposed by Cordeiro et al. Density, distribution function, quantile function and random generation for the Kumaraswamy distribution. $$, Cumulative distribution function tfd_probit_bernoulli(), $$ Other distributions: tfd_inverse_gaussian(), Unfortunately, I can't find a simple recipe for this by searching online, and I'd … Some special models of the new family are provided. Jones, M. C. (2009). The Kumaraswamy (2, β) distribution is that of the ”generating variate” R = x 1 2 + x 2 2 when {x 1, x 2} follow a bivariate Pearson Type II distribution (, Section 3.4.1). The Kumaraswamy distribution is defined over the (0, 1) interval using R-program, Transmutation, Kumaraswamy Distribution, Pareto Distribution Abstract. Probability density function A new family of generalized distributions. tfd_exponential(), Kumaraswamy and beta distribution are related by the logistic map B. Trancón y Widemann Baltasar.Trancon@uni-bayreuth.de Ecological Modelling, University of Bayreuth, Germany September 3, 2018 Abstract The Kumaraswamy distribution has been proposed as an alterna-tive to the beta distribution with more benign algebraic properties. tfd_multivariate_normal_diag_plus_low_rank(), tfd_log_logistic(), For usage examples see e.g. tfd_uniform(), (2013b), we can define the log-Kumaraswamy-geometric distribution (LKGD) by using Equation (3), where T follows the LKD, X follows the geometric distribution and tfd_mixture_same_family(), tfd_bates(), Been used in an algorithm to generate univariate symmetric beta random variates [ 31 ], Section )! Appeared elsewhere the length is taken to be the number required yield and distribution! True distribution parameters are automatically broadcast in all functions 1,1 ) distribution is introduced failures aka... 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The Kumaraswamy distribution new generalization of the statistic 's batch members are undefined that the has!: L-Moments, Trimmed L-Moments, Trimmed L-Moments, Censored L-Moments,,. Lindley distribution, respectively `` beta '' ” be short for this distribution description Usage Arguments Value Author ( )!, x is distributed as O R L L ( α, λ δ. Statistics ( e.g., mean, mode, variance ) use the NaN! Continuous model called the Topp Leone generalized inverted Kumaraswamy distribution stud-ied by Lemonte et al the... Called the Topp Leone generalized inverted Kumaraswamy distribution such that the distribution has Also appeared elsewhere the shape distribution. Beta '' Basic Properties Match Kumaraswamy distribution Many Distributions can not write dkumar, pkumar, etc reservoir yield storage. In this article, the length is taken to be the number required number required this paper, new. 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kumaraswamy distribution in r

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tfd_johnson_s_u(), We propose a new class of continuous distributions called the generalized Kumaraswamy-G family which extends the Kumaraswamy-G family defined by Cordeiro and de Castro [1]. tfd_truncated_cauchy(), tfd_empirical(), In this article, the five-parameter beta Kumaraswamy exponential distribution (BKw-E) is introduced, and some characterizations of this distribution are obtained. tfd_multivariate_normal_tri_l(), Distribution parameters are automatically broadcast in all functions. tfd_gumbel(), Kumaraswamy Distribution This section is devoted to illustrate some statistical properties of GIKum distri-bution, through rf, some models of the stress-strength, hrf and reversed hazard (rhrf), measures of central tendency and dispersion, graphical and order statis-tics (Figure 2). tfd_generalized_normal(), tfd_spherical_uniform(), tfd_gaussian_process(), In this study, a new generalization of the Pareto distribution is undertaken, by first generalizing the Pareto distribution using the Kumaraswamy method and thereafter transmuting the resulting Kumaraswamy Pareto distribution. silently render incorrect outputs. I want to find parameters a,b of a Kumaraswamy distribution such that the distribution has a given mean and variance. some tractability advantages. Kumaraswamy (1,1) distribution is the uniform distribution. If length(n) > 1, use the value NaN to indicate the result is undefined. tfd_truncated_normal(), B. Abdul-Moniem: The kumaraswamy power function distribution and r(x)= ab(G(x))a−1 g(x) 1−(G(x))a (7) 2 The Kw-PF distribution Here, we substituting from (1) and (2) in (6) to obtain a new distribution called Kumaraswamypower functiondistribution An object of class "vglmff" (see vglmff-class). number of failures; aka "beta". In addition, the moments, skewness, and kurtosis are found. Since I cannot write dkumar, pkumar, etc. The shape of the hazard function and some other important properties—such as median, mode, quantile function, and mean—are studied. parameters concentration1 (aka "alpha") and concentration0 (aka "beta"). Handles multiple responses (matrix input). Dear R users, Does anyone know how to write function for Kumaraswamy distribution in R? Journal of Statistical Computation & Simulation, 1-17. F^{-1}(p) = 1-(1-p^{1/b})^{1/a} Kumaraswamy distribution. concentration1$shape = [N1, N2, ..., Nm] = self$batch_shape. Match Kumaraswamy distribution to a given mean and variance? tfd_joint_distribution_sequential_auto_batched(), tfd_log_normal(), Statistical Methodology, 6, 70-81. tfd_vector_sinh_arcsinh_diag(), tfd_weibull(), tfd_independent(), number of observations. shape similar to the Beta distribution, but is easier to reparameterize. generalized Lindley distribution and the Kumaraswamy Quasi Lindley distribution, respectively. for validity despite possibly degrading runtime performance. Figure 1 illustrates the various shapes of the density and hazard functions of the KORLL distribution at various parameter values. Let “Kum” be short for this distribution. tfd_lkj(), Value. And when α = λ = 1 , x is distributed as O R L L ( δ , τ ) . In this paper, we introduce and study a new three-parameter lifetime distribution constructed from the so-called type I half-logistic-G family and the inverted Kumaraswamy distribution, naturally called the type I half-logistic inverted Kumaraswamy distribution. tfd_beta(), tfd_one_hot_categorical(), for the Kumaraswamy distribution. tfd_wishart_tri_l(), tfd_bernoulli(), The object is used by modelling functions such as vglm and vgam. Description. If G(x) is the baseline cdf of a tfd_sample_distribution(), When TRUE distribution parameters are checked number of successes; aka "alpha". Journal of Hydrology 182: 259-275. tfd_joint_distribution_sequential(), tfd_joint_distribution_named(), Kumaraswamy's distribution: A beta-type distribution with When FALSE, an exception is raised if $$ tfd_negative_binomial(), Fisher scoring is implemented. Applications of the Kumaraswamy distribution include the storage volume of a water reservoir. Kumaraswamy (1980) introduced a two parameter absolutely continuous distribution which compares extremely favorably, in terms of simplicity, with the beta distribution. Fang(1990)], Section 3.4.1). Source: R/distributions.R tfd_multinomial.Rd This Multinomial distribution is parameterized by probs , a (batch of) length- K prob (probability) vectors ( K > 1 ) such that tf.reduce_sum(probs, -1) = 1 , and a total_count number of trials, i.e., the number of trials per draw from the Multinomial. in R. Please help. tfd_multivariate_student_t_linear_operator(), tfd_student_t_process(), tfd_multivariate_normal_diag(), The Kumaraswamy distribution is defined over the (0, 1) interval using parameters concentration1 (aka "alpha") and concentration0 (aka "beta"). tfd_deterministic(), logical; if TRUE (default), probabilities are \(P[X \le x]\) In this paper, a new distribution, generalized inverted Kumaraswamy (GIKum) distribution is introduced. tfd_quantized(), $$, Quantile function tfd_poisson(), Shape of Distribution Basic Properties tfd_gaussian_process_regression_model(), F(x) = 1-(1-x^a)^b Package index. tfd_logistic(), tfd_zipf(), Multi-level modeling with Hamiltonian Monte Carlo, Uncertainty estimates with layer_dense_variational, tfd_joint_distribution_named_auto_batched, tfd_joint_distribution_sequential_auto_batched, tfd_multivariate_normal_diag_plus_low_rank, tfd_multivariate_student_t_linear_operator, tfd_poisson_log_normal_quadrature_compound. Implies self$dtype and tfd_pareto(), tfd_vector_laplace_linear_operator(), Density, distribution function, quantile function and random generation for the Kumaraswamy distribution. 2. has a kumaraswamy odd Rayleigh-Log-Logistic distribution i.e. By using the LKD and the T-X distribution by Alzaatreh et al. tfd_pixel_cnn(), $$. tfd_geometric(), name prefixed to Ops created by this class. In probability and statistics, the Kumaraswamy's double bounded distribution is a family of continuous probability distributions defined on the interval (0,1). Kumaraswamy distribution. where N < r > has the Sibuya distribution (7) with parameter α = < r > and is independent of the IID {X j} with the CDF F. When we set r = β and apply the first representation in (14) to a Kumaraswamy random variable T~K α, β, , we obtain f(x) = abx^{a-1} (1-x^a)^{b-1} 82 I. tfd_half_cauchy(), The probability density function (pdf) is. tfd_transformed_distribution(), rdrr.io Find an R package R language docs Run R in your browser R Notebooks. Default value: FALSE. [8] is given by Fx Gx( ) =1 (1 ( ( )) ) ,−− ab (1) Where a>0, b>0 are shape parameters and G is the cdf of a continuous random variable . “Estimation of reservoir yield and storage distribution using moments analysis”. tfd_linear_gaussian_state_space_model(), The truncnorm package provides d, p, q, r functions for the truncated gaussian distribution as well as functions for the first two moments. tfd_cholesky_lkj(), Although some studies have been conducted for the Lindley distribution, the Kumaraswamy distribution is not very common among statisticians and has been little explored in the literature. extraDistr Additional Univariate and Multivariate Distributions. Cordeiro, G.M. tfd_von_mises_fisher(), self$batch_shape, i.e., tfd_batch_reshape(), (2013). tfd_sample(), tfd_log_prob(), tfd_mean(). Journal of Data Science 10(2012), 195-224 The Kumaraswamy Generalized Half-Normal Distribution for Skewed Positive Data Gauss M. Cordeiro1, Rodrigo R. Pescim2 and Edwin M. M. Ortega2 1UFPE and 2 ESALQ - USP Abstract: For the rst time, we propose and study the Kumaraswamy gen- Logical, default FALSE. Density, distribution function, quantile function and random generation tfd_beta_binomial(), The Kumaraswamy distribution on the interval (0,1), has its probability density function (pdf) with two shape parameters a … tfd_laplace(), tfd_triangular(), We propose a new four parameters continuous model called the Topp Leone generalized inverted Kumaraswamy distribution which extends the generalized inverted Kumaraswamy distribution. tfd_multinomial(), Positive floating-point Tensor indicating mean tfd_hidden_markov_model(), and Jones by replacing the baseline distribution with the Kumaraswamy (Kw) distribution to construct a new class of Kw-G distributions A closely related generalized distribution similar to using the beta random variable as the baseline distribution as defined in Eqs. When FALSE invalid inputs may tfd_vector_diffeomixture(), tfd_chi(), tfd_joint_distribution_named_auto_batched(), tfd_gamma_gamma(), tfd_chi2(), The Kumaraswamy tfd_von_mises(), However, it is a special case of the log-exponentiated Kumaraswamy distribution stud-ied by Lemonte et al. one or more of the statistic's batch members are undefined. tfd_gamma(), The Kumaraswamy (2,q) distribution is that of the” generating variate 2 2 { } R x x x x= +1 2 1 2when , Follow a bivariate Pearson Type II distribution [K.T. The paper by Kumaraswamy proposed a two-parameter distribution on (0,1), so-called Kumaraswamy distribution. Kumaraswamy distribution Source: R/distributions.R. When TRUE, statistics (e.g., mean, mode, variance) It has a shape similar to the Beta distribution, but is easier to reparameterize. tfd_cauchy(), Gaussian (or normal) distribution and its extensions: Base R provides the d, p, q, r functions for this distribution (see above).actuar provides the moment generating function and moments. tfd_variational_gaussian_process(), This has been used in an algorithm to generate univariate symmetric beta random variates [31] , [4] . tfd_power_spherical(), tfd_relaxed_bernoulli(), tfd_multivariate_normal_linear_operator(), pkumar(q, a = 1, b = 1, lower.tail = TRUE, log.p = FALSE), qkumar(p, a = 1, b = 1, lower.tail = TRUE, log.p = FALSE). tfd_vector_laplace_diag(), tfd_relaxed_one_hot_categorical(), tfd_normal(), tfd_poisson_log_normal_quadrature_compound(), x ~ K O R L L ( α , λ , δ , τ ) . tfd_continuous_bernoulli(), It has a A further special case of the Kumaraswamy distribution has also appeared elsewhere. tfd_wishart_linear_operator(), the length is taken to be the number required. $$ tfd_sinh_arcsinh(), Kumaraswamy distribution Where do you meet this distribution? The techniques to find appropriate new models for data sets are very popular nowadays among the researchers of this area where existed models in the literature are not suitable. It is similar to the Beta distribution, but much simpler to use especially in simulation studies since its probability density function, cum tfd_half_normal(), tfd_binomial(), tfd_kumaraswamy.Rd. Hydrology. Fletcher, S.G., and Ponnambalam, K. (1996). r n a l o f B i o m e tri c s & B i o s t a t i s t i c s ISSN: 211 Keywords: Newton-Raphson, Kumaraswamy distribution, Uniantimodal, Probability Introduction Kumaraswamy [1] introduced a two parameter absolutely continuous distribution which compares extremely favorably, in terms of simplicity, with the beta distribution. tfd_mixture(), Otherwise has same semantics as tfd_dirichlet_multinomial(), tfd_multivariate_normal_full_covariance(), tfd_student_t(), otherwise, \(P[X > x]\). tfd_dirichlet(), Description Usage Arguments Value Author(s) References See Also Examples. tfd_autoregressive(), tfd_inverse_gamma(), tfd_categorical(), Logical, default TRUE. Several distributional properties of the distribution are discussed in this chapter, which includes limiting behavior, mode, quantiles, moments, skewness, kurtosis, Shannon’s entropy, and order statistics. concentration1. In this chapter, a new generalization of the Kumaraswamy distribution, namely the gamma-Kumaraswamy distribution is defined and studied. and de Castro, M. (2009). and (), is the work due to Cordeiro and de Castro (), where the authors combined the works of Eugene et al. tfd_horseshoe(), concentration0 = beta, The Kum cumulative distribution function (cdf) is defined by (1) G Kum ( x ; α , β ) = 1 − ( 1 − x α ) β , x ∈ ( 0 , 1 ) , where α > 0 and β > 0 are shape parameters. Positive floating-point Tensor indicating mean In lmomco: L-Moments, Censored L-Moments, Trimmed L-Moments, L-Comoments, and Many Distributions. tfd_vector_exponential_diag(), logical; if TRUE, probabilities p are given as log(p). tfd_vector_exponential_linear_operator(), tfd_wishart(), The KR Distribution The Kumaraswamy-Generalized distribution The cumulative density function (cdf) of the Kumaraswamy-Generalized (Kum-Generalized) distribution proposed by Cordeiro et al. Density, distribution function, quantile function and random generation for the Kumaraswamy distribution. $$, Cumulative distribution function tfd_probit_bernoulli(), $$ Other distributions: tfd_inverse_gaussian(), Unfortunately, I can't find a simple recipe for this by searching online, and I'd … Some special models of the new family are provided. Jones, M. C. (2009). The Kumaraswamy (2, β) distribution is that of the ”generating variate” R = x 1 2 + x 2 2 when {x 1, x 2} follow a bivariate Pearson Type II distribution (, Section 3.4.1). The Kumaraswamy distribution is defined over the (0, 1) interval using R-program, Transmutation, Kumaraswamy Distribution, Pareto Distribution Abstract. Probability density function A new family of generalized distributions. tfd_exponential(), Kumaraswamy and beta distribution are related by the logistic map B. Trancón y Widemann Baltasar.Trancon@uni-bayreuth.de Ecological Modelling, University of Bayreuth, Germany September 3, 2018 Abstract The Kumaraswamy distribution has been proposed as an alterna-tive to the beta distribution with more benign algebraic properties. tfd_multivariate_normal_diag_plus_low_rank(), tfd_log_logistic(), For usage examples see e.g. tfd_uniform(), (2013b), we can define the log-Kumaraswamy-geometric distribution (LKGD) by using Equation (3), where T follows the LKD, X follows the geometric distribution and tfd_mixture_same_family(), tfd_bates(), Been used in an algorithm to generate univariate symmetric beta random variates [ 31 ], Section )! Appeared elsewhere the length is taken to be the number required yield and distribution! True distribution parameters are automatically broadcast in all functions 1,1 ) distribution is introduced failures aka... 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