Covariance Model Research Articles

Pengaruh Stres Kerja, Kepuasan Kerja, Dan Komitmen Organsiasi Terhadap Niat Pindah Pekerjaan

Research conducted by Prasetio et al. (2018) found that there was no significant relationship between job stress and job satisfaction. This study aims to examine the relationship between job satisfaction, job stress, organizational commitment and turnover intention. This research was conducted at one of the securities companies in Jakarta named PT. Sucor Sekuritas, which experienced an increase in the number of employees leaving from 2020-2021. The population of this research is the employees of PT. Sucor Sekuritas with a purposive sampling research sample. The source of this research data is secondary data obtained from companies and primary data obtained from a questionnaire survey using google form. The analysis of this research uses Variance based Structural Equation Model using Partial Least Square (Smart-pls) program with an alternative model of covariance based Structural Equation Model with outer model and inner model, as well as descriptive analysis with Three Box Methode. The results obtained in this study are job stress affects the intention to change jobs, job satisfaction and organizational commitment. Then there was no effect of job satisfaction on the intention to change jobs, there was no effect of organizational commitment on the intention to change jobs, and there was no effect of job satisfaction and organizational commitment as intervening variables between job stress and turnover intention.

Decays B→D(s)(*)h ( h=π , ρ ) in a confined covariant quark model

Decay processes $B\ensuremath{\rightarrow}{D}_{(s)}^{(*)}h$ ($h=\ensuremath{\pi}$, $\ensuremath{\rho}$) are studied in the framework of the confined covariant quark model using the na\"{\i}ve factorization assumption. We observe that the theoretical results on branching fractions have a tendency to systematically exceed the experimental numbers. Such a behavior has already been seen for similar processes by other authors.

Ionospheric Kalman Filter Assimilation Based on Covariance Localization Technique

The data assimilation algorithm is a common algorithm in space weather research. Based on the GNSS data from the China Crustal Movement Observation Network (CMONOC) and the International Reference Ionospheric Model (IRI), a fast three-dimensional (3D) electron density nowcasting model for China and its adjacent regions was developed. Unlike the traditional Gaussian background covariance model, the error covariance of the IRI model, based on the IGS grid TEC data, is estimated in this work. Due to the large scale of the high-resolution covariance matrix, it cannot be stored and calculated directly on a personal computer. The covariance localization (CL) technique is introduced to sparse the covariance matrix while removing the pseudo-correlation of the covariance matrix. After localization, the covariance matrix can be converted into a sparse matrix for storage and calculation, which greatly reduces the computer memory requirement of the assimilation model and improves the calculation speed of the model. Based on this algorithm, a series of experiments were carried out in this work. The experimental results show that this algorithm can effectively assimilate the observed GNSS to the background field, make up for the temporal and spatial limitations of the observed data, and improve the accuracy of the ionospheric electron density nowcast. Compared with the digisonde observed foF2 (the critical frequency of the ionospheric F2 layer), the RMSE of the assimilation model is 0.44 MHz lower than that of the IRI model.

Hybrid ensemble-variational data assimilation in ABC-DA within a tropical framework

Abstract. Hybrid ensemble-variational data assimilation (DA) methods have gained significant traction in recent years. These methods aim to alleviate the limitations and maximise the advantages offered by ensemble or variational methods. Most existing hybrid applications focus on the mid-latitudinal context; almost none have explored its benefits in the tropical context. In this article, hybrid ensemble-variational DA is introduced to a tropical configuration of a simplified non-hydrostatic convective-scale fluid dynamics model (the ABC model, named after its three key parameters: the pure gravity wave frequency A, the controller of the acoustic wave speed B, and the constant of proportionality between pressure and density perturbations C), and its existing variational framework, the ABC-DA system. The hybrid ensemble-variational DA algorithm is developed based on the alpha control variable approach, often used in numerical weather prediction. Aspects of the algorithm such as localisation (used to mitigate sampling error caused by finite ensemble sizes) and weighting parameters (used to weight the ensemble and climatological contributions to the background error covariance matrix) are implemented. To produce the flow-dependent error modes (ensemble perturbations) for the ensemble-variational DA algorithm, an ensemble system is also designed for the ABC model which is run alongside the hybrid DA system. A random field perturbations method is used to generate an initial ensemble which is then propagated using the ensemble bred vectors method. This setup allows the ensemble to be centred on the hybrid control analysis. Visualisation software has been developed to focus on the diagnosis of the ensemble system. To demonstrate the hybrid ensemble-variational DA in the ABC-DA system, sensitivity tests using observing system simulation experiments are conducted within a tropical framework. A 30-member ensemble was used to generate the error modes for the experiments. In general, the best performing configuration (with respect to the “truth”) for the hybrid ensemble-variational DA system used an 80%/20% weighting on the ensemble-derived/climatological background error covariance matrix contributions. For the horizontal wind variables though, full weight on the ensemble-derived background error covariance matrix (100%/0%) resulted in the smallest cycle-averaged analysis root mean square errors, mainly due to large errors in the meridional wind field when contributions from the climatological background error covariance matrix were involved, possibly related to a sub-optimal background error covariance model. The ensemble bred vectors method propagated a healthy-looking DA-centred ensemble without bimodalities or evidence of filter collapse. The ensemble was under-dispersive for some variables but for others, the ensemble spread approximately matched the corresponding root mean square errors. Reducing the number of ensemble members led to slightly larger errors across all variables due to the introduction of larger sampling errors into the system.

Efficacy of a loading dose of IV salbutamol in children with severe acute asthma admitted to a PICU: a randomized controlled trial

The optimal dose regimen for intravenous (IV) treatment in children with severe acute asthma (SAA) is still a matter of debate. We assessed the efficacy of adding a salbutamol loading dose to continuous infusion with salbutamol in children admitted to a pediatric intensive care unit (PICU) with SAA. This multicentre, placebo-controlled randomized trial in the PICUs of four tertiary care children’s hospitals included children (2–18 years) with SAA admitted between 2017 and 2019. Children were randomized to receive either a loading dose IV salbutamol (15 mcg/kg, max. 750 mcg) or normal saline while on continuous salbutamol infusion. The primary outcome was the asthma score (Qureshi) 1 h after the intervention. Analysis of covariance models was used to evaluate sensitivity to change in asthma scores. Serum concentrations of salbutamol were obtained. Fifty-eight children were included (29 in the intervention group). Median baseline asthma score was 12 (IQR 10–13) in the intervention group and 11 (9–12) in the control group (p = 0.032). The asthma score 1 h after the intervention did not differ significantly between the groups (p = 0.508, β-coefficient = 0.283). The median increase in salbutamol plasma levels 10 min after the intervention was 13 μg/L (IQR 5–24) in the intervention group and 4 μg/L (IQR 0–7) in the control group (p = 0.001). Side effects were comparable between both groups.Conclusion: We found no clinical benefit of adding a loading dose IV salbutamol to continuous infusion of salbutamol, in children admitted to the PICU with SAA. Clinically significant side effects from the loading dose were not encountered.What is Known:• Pediatric asthma guidelines struggle with an evidence-based approach for the treatment of SAA beyond the initial steps of oxygen suppletion, repetitive administration of inhaled β2-agonists, and systemic steroids.• During an SAA episode, effective delivery of inhaled drugs is unpredictable due to severe airway obstruction.What is New:• This study found no beneficial effect of an additional loading dose IV salbutamol in children admitted to the PICU.• This study found no clinically significant side effects from the loading dose.

Add-On Pramipexole for the Treatment of Schizophrenia and Schizoaffective Disorder: A Randomized Controlled Trial.

Objective: Several small clinical trials have reported that the dopamine agonist pramipexole was beneficial in treating patients with schizophrenia. A confirmatory trial was conducted to test this hypothesis.Methods: This 16-week, multicenter, double-blind, randomized, placebo-controlled study included 200 subjects meeting DSM-IV-TR criteria for schizophrenia or schizoaffective disorder. Patients were randomized to receive either pramipexole (0.75 mg twice daily, n = 100) or placebo (n = 100) as an add-on to their regular antipsychotic treatment. The primary outcome measure was the total score on the Positive and Negative Syndrome Scale (PANSS); secondary outcome measures included PANSS subscale and cognitive functioning scores. Recruitment was performed in 30 sites in Romania and 1 site in the Republic of Moldova between January and June 2011.Results: Analysis of covariance models showed no significant difference between pramipexole and placebo for total PANSS (P > .99) and PANSS positive (P > .99), negative (P = .73), and general psychopathology (P = .99) subscale scores. Changes in Clinical Global Impressions-Severity of Illness scale and Brief Assessment of Cognition in Schizophrenia scores showed no significant difference between pramipexole and placebo.Conclusions: The results of this large randomized controlled trial indicated that pramipexole was not efficacious as an add-on to antipsychotic medications for schizophrenia.Trial Registration: ClinicalTrials.gov identifier NCT01320982.

TensorGraphicalModels: A Julia toolbox for multiway covariance models and ensemble Kalman filter

<h2>Abstract</h2> The increasing availability of high dimensional multi-indexed data has created an opportunity for the development of graphical modeling software that bridges the gap between second order statistical and computational models. In this paper, we introduce TensorGraphicalModels, a suite of Julia tools for statistical estimation of high-dimensional multiway (tensor-variate) covariance and precision matrices, with applications to ensemble Kalman filtering. The Julia package implements several state-of-the-art multiway covariance and precision matrix estimators. These are illustrated in the context of a physics-driven forecasting example with an integrated implementation of a tensor ensemble Kalman filter (EnKF).

Asymptotic independence of spiked eigenvalues and linear spectral statistics for large sample covariance matrices

We consider general high-dimensional spiked sample covariance models and show that their leading sample spiked eigenvalues and their linear spectral statistics are asymptotically independent when the sample size and dimension are proportional to each other. As a byproduct, we also establish the central limit theorem of the leading sample spiked eigenvalues by removing the block diagonal assumption on the population covariance matrix, which is commonly needed in the literature. Moreover, we propose consistent estimators of the L4 norm of the spiked population eigenvectors. Based on these results, we develop a new statistic to test the equality of two spiked population covariance matrices. Numerical studies show that the new test procedure is more powerful than some existing methods.

Cardiovascular effects of dobutamine, norepinephrine and phenylephrine in isoflurane-anaesthetized dogs administered dexmedetomidine–vatinoxan

ObjectiveTo determine whether dobutamine, norepinephrine or phenylephrine infusions alleviate hypotension in isoflurane-anaesthetized dogs administered dexmedetomidine with vatinoxan. Study designBalanced, randomized crossover trial. AnimalsA total of eight healthy Beagle dogs. MethodsEach dog was anaesthetized with isoflurane (end-tidal isoflurane 1.3%) and five treatments: dexmedetomidine hydrochloride (2.5 μg kg–1) bolus followed by 0.9% saline infusion (DEX-S); dexmedetomidine and vatinoxan hydrochloride (100 μg kg–1) bolus followed by an infusion of 0.9% saline (DEX-VAT-S), dobutamine (DEX-VAT-D), norepinephrine (DEX-VAT-N) or phenylephrine (DEX-VAT-P). The dexmedetomidine and vatinoxan boluses were administered at baseline (T0) and the treatment infusion was started after 15 minutes (T15) if mean arterial pressure (MAP) was < 90 mmHg. The treatment infusion rate was adjusted every 5 minutes as required. Systemic haemodynamics were recorded at T0 and 10 (T10) and 45 (T45) minutes. A repeated measures analysis of covariance model was used. ResultsMost dogs had a MAP < 70 mmHg at T0 before treatment. Treatments DEX-S and DEX-VAT all significantly increased MAP at T10, but systemic vascular resistance index (SVRI) was significantly higher and cardiac index (CI) lower after DEX-S than after DEX-VAT. CI did not significantly differ between DEX-S and DEX-VAT-S at T45, while SVRI remained higher with DEX-S. Normotension was achieved by all vasoactive infusions in every dog, whereas MAP was below baseline with DEX-VAT-S, and higher than baseline with DEX-S at T45. Median infusion rates were 3.75, 0.25 and 0.5 μg kg–1 minute–1 for dobutamine, norepinephrine and phenylephrine, respectively. Dobutamine and norepinephrine increased CI (mean ± standard deviation, 3.35 ± 0.70 and 3.97 ± 1.24 L minute–1 m–2, respectively) and decreased SVRI, whereas phenylephrine had the opposite effect (CI 2.13 ± 0.45 L minute–1 m–2). Conclusions and clinical relevanceHypotension in isoflurane-anaesthetized dogs administered dexmedetomidine and vatinoxan can be treated with either dobutamine or norepinephrine.

The effect of IV ketamine in patients with major depressive disorder and elevated features of borderline personality disorder

BackgroundComorbid borderline personality disorder and major depressive disorder is common and often not adequately responsive to standard antidepressant therapies. Ketamine is a potentially life-saving option. Methods153 adult patients with MDD were assessed with the Personality Assessment Inventory (PAI) Borderline Subscale. Data was normally distributed with a mean + SD of 38.95 + 11.54. Patients >1 SD above the mean were assigned to the MDD + BF group. All others were assigned to the MDD–BF group. Patients were administered IV ketamine 0.5 mg/kg of ketamine over 40 min. Mood was assessed using the Beck Depression Inventory-II at baseline, 3 and 24 h post-ketamine. Scores between the MDD + BF and MDD–BF group at each time point were compared using t-test or analysis of covariance (ANCOVA) model. The primary outcome was response at 24 h. ResultsThe LS mean change in BDI at 24 h was −23.8 (15.3) for MDD + BF and −21.0 (13.5) for MDD–BF (F [1151] = 0.043, p = 0.51). The LS mean change in BDI at 3 h was −21.3 (13.2) for MDD + BF and −19.6 (13.2) for MDD–BF (F[1151] = 0.045, p = 0.83). The LS mean change in BDI at 14 days was −23.2 (15.3) for MDD + BF and −15.3 (15.2) for MDD–BF (F[1130] = 4.24, p = 0.04). LimitationsPeople in the MDD + BF group were not necessarily diagnosable with borderline personality disorder. ConclusionsThese data indicate that IV ketamine is effective in MDD patients with and without elevated borderline features. This can provide clinicians some reassurance about using ketamine in this population.

Relationships Among Pay-for-Performance, Work Stressors, and Depression in Sales Workers: A Structural Equation Model Analysis.

The aim of this study was to examine whether pay-for-performance (PFP) affects depression via work stressors. This study used data from self-administered questionnaires obtained from 1160 sales workers, and the data were analyzed using structural equation modeling (covariance structure analysis). Models included "long hour labor condition (LHLC)," which consisted of the number of working hours, hours worked per month, service overtime, and increase or decrease in working hours; seven work stressors; and the Center for Epidemiologic Studies Depression scale. According to the final model (CFI = 0.950, RMSEA = 0.035), PFP worsened LHLC (standardized total effect [STE] = 0.357) and improved job control (STE = 0.108), and although slightly, exacerbated depression via other work stressors (STE = 0.051). Our results suggest the need for measures to avoid prolonged overwork to prevent worsening of employee mental health when introducing or implementing PFP.

Designing three-level cluster randomized trials to assess treatment effect heterogeneity.

Cluster randomized trials often exhibit a three-level structure with participants nested in subclusters such as health care providers, and subclusters nested in clusters such as clinics. While the average treatment effect has been the primary focus in planning three-level randomized trials, interest is growing in understanding whether the treatment effect varies among prespecified patient subpopulations, such as those defined by demographics or baseline clinical characteristics. In this article, we derive novel analytical design formulas based on the asymptotic covariance matrix for powering confirmatory analyses of treatment effect heterogeneity in three-level trials, that are broadly applicable to the evaluation of cluster-level, subcluster-level, and participant-level effect modifiers and to designs where randomization can be carried out at any level. We characterize a nested exchangeable correlation structure for both the effect modifier and the outcome conditional on the effect modifier, and generate new insights from a study design perspective for conducting analyses of treatment effect heterogeneity based on a linear mixed analysis of covariance model. A simulation study is conducted to validate our new methods and two real-world trial examples are used for illustrations.

Nonsingular spherically symmetric black-hole model with holonomy corrections

We present a covariant model of a spherically symmetric black hole with corrections motivated by loop quantum gravity. The effective modifications, parametrized by a positive constant $\ensuremath{\lambda}$, are implemented through a canonical transformation and a linear combination of the constraints of general relativity, in such a way that the theory remains free of anomalies and general relativity is recovered for $\ensuremath{\lambda}=0$. In addition, the corresponding metric is constructed in a fully covariant way to ensure that gauge transformations on phase space correspond to coordinate changes. The solution for each gauge choice provides a chart and corresponding line element of a spacetime solution whose geometry is unambiguously determined in terms of the parameter $\ensuremath{\lambda}$ and a constant of motion $m$. For positive values of $m$, the solution is asymptotically flat and contains a globally hyperbolic black-hole/white-hole region with a minimal spacelike hypersurface that replaces the Schwarzschild singularity. The corresponding exterior regions are isometric and, in particular, allow the computation of the Arnowitt-Deser-Misner mass. The procedure to obtain the global causal structure of the solution yields also its maximal analytic extension.

Cognitive function with evolocumab in pediatric heterozygous familial hypercholesterolemia

Evolocumab is a fully human monoclonal antibody inhibitor of PCSK9 approved for lowering low-density lipoprotein cholesterol in adults and pediatric patients with familial hypercholesterolemia (FH). The cognitive safety of evolocumab has been established in adults but has not yet been described in pediatric patients. To determine the effects of evolocumab on cognitive function in pediatric heterozygous FH. Cognitive function was assessed during a 24-week, randomized, double-blind, placebo-controlled study (HAUSER-RCT) evaluating the efficacy, safety, and tolerability of 24 weeks of monthly subcutaneous injections of evolocumab in pediatric patients with FH. Cognitive safety endpoints included changes from baseline to week 24 in test scores in domains of psychomotor function, attention, visual learning, and executive function. Between-group differences in age-standardized mean test score changes were analyzed using analysis of covariance models and point estimates with 95% confidence interval (CI). Magnitudes of difference between treatment groups (Cohen's d) and reliable change indices were calculated for each cognitive function test. At week 24, changes from baseline in age-standardized cognitive test scores were similar between the treatment groups. Differences (95% CI) between the evolocumab and placebo groups in mean test score changes for the Groton Maze Learning, One-Card Learning, Identification, and Detection tests were 0.1 (-0.2, 0.4), -0.1 (-0.5, 0.4), 0.3 (0.0, 0.7), 0.3 (-0.1, 0.8), respectively. For all tests, abnormal and clinically important cognitive decline occurred with lesser frequency in the evolocumab group. In pediatric patients with FH, 24-week treatment with evolocumab did not negatively influence cognition. This study was funded and designed by Amgen.

PtRNAdb: a web resource of plant tRNA genes from a wide range of plant species.

The online version contains supplementary material available at 10.1007/s13205-022-03255-7.

The Debiased Spatial Whittle likelihood.

We provide a computationally and statistically efficient method for estimating the parameters of a stochastic covariance model observed on a regular spatial grid in any number of dimensions. Our proposed method, which we call the Debiased Spatial Whittle likelihood, makes important corrections to the well-known Whittle likelihood to account for large sources of bias caused by boundary effects and aliasing. We generalize the approach to flexibly allow for significant volumes of missing data including those with lower-dimensional substructure, and for irregular sampling boundaries. We build a theoretical framework under relatively weak assumptions which ensures consistency and asymptotic normality in numerous practical settings including missing data and non-Gaussian processes. We also extend our consistency results to multivariate processes. We provide detailed implementation guidelines which ensure the estimation procedure can be conducted in operations, where n is the number of points of the encapsulating rectangular grid, thus keeping the computational scalability of Fourier and Whittle-based methods for large data sets. We validate our procedure over a range of simulated and realworld settings, and compare with state-of-the-art alternatives, demonstrating the enduring practical appeal of Fourier-based methods, provided they are corrected by the procedures developed in this paper.

Effects of Structured Supervised Exercise Training or Motivational Counseling on Pregnant Women's Physical Activity Level: FitMum - Randomized Controlled Trial.

BackgroundPhysical activity (PA) during pregnancy is an effective and safe way to improve maternal health in uncomplicated pregnancies. However, compliance with PA recommendations remains low among pregnant women.ObjectiveThe purpose of this study was to evaluate the effects of offering structured supervised exercise training (EXE) or motivational counseling on PA (MOT) during pregnancy on moderate-to-vigorous intensity physical activity (MVPA) level. Additionally, complementary measures of PA using the Pregnancy Physical Activity Questionnaire (PPAQ) and gold standard doubly labeled water (DLW) technique were investigated. The hypotheses were that both EXE and MOT would increase MVPA in pregnancy compared with standard care (CON) and that EXE would be more effective than MOT. In addition, the association between MVPA and the number of sessions attended was explored.MethodsA randomized controlled trial included 220 healthy, inactive pregnant women with a median gestational age of 12.9 (IQR 9.4-13.9) weeks. A total of 219 women were randomized to CON (45/219), EXE (87/219), or MOT (87/219). The primary outcome was MVPA (minutes per week) from randomization to the 29th gestational week obtained by a wrist-worn commercial activity tracker (Vivosport, Garmin International). PA was measured by the activity tracker throughout pregnancy, PPAQ, and DLW. The primary outcome analysis was performed as an analysis of covariance model adjusting for baseline PA.ResultsThe average MVPA (minutes per week) from randomization to the 29th gestational week was 33 (95% CI 18 to 47) in CON, 50 (95% CI 39 to 60) in EXE, and 40 (95% CI 30 to 51) in MOT. When adjusted for baseline MVPA, participants in EXE performed 20 (95% CI 4 to 36) minutes per week more MVPA than participants in CON (P=.02). MOT was not more effective than CON; EXE and MOT also did not differ. MVPA was positively associated with the number of exercise sessions attended in EXE from randomization to delivery (P=.04). Attendance was higher for online (due to COVID-19 restrictions) compared with physical exercise training (P=.03). Adverse events and serious adverse events did not differ between groups.ConclusionsOffering EXE was more effective than CON to increase MVPA among pregnant women, whereas offering MOT was not. MVPA in the intervention groups did not reach the recommended level in pregnancy. Changing the intervention to online due to COVID-19 restrictions did not affect MVPA level but increased exercise participation.Trial RegistrationClinicalTrials.gov NCT03679130; https://clinicaltrials.gov/ct2/show/NCT03679130International Registered Report Identifier (IRRID)RR2-10.1136/bmjopen-2020-043671

Conditions on which cokriging does not do better than kriging

There is a vast literature on analyzing univariate spatial data by modeling, inference, and prediction in the past decades. While statistical modeling and inference with multivariate spatial data have been well developed, spatial prediction using multivariate spatial data called cokriging is relatively less investigated. Cokriging is usually considered to be superior to kriging, but there are not many theoretical studies that investigate how good cokriging is over kriging or when cokriging does not better than kriging. In this work, we provide explicit conditions on the covariance parameters and sampling schemes under an intrinsic coregionalization covariance model, with which cokriging does not better than kriging. Simulation studies and real data examples are also introduced to support our theoretical findings.

Sperm characteristics in normal and abnormal ejaculates are differently influenced by the length of ejaculatory abstinence.

No association between the length of ejaculatory abstinence (LEA) and semen characteristics has been confirmed. A short LEA has been linked to improved sperm characteristics and a higher pregnancy rate, but its negative influence on sperm chromatin maturity and longevity may adversely affect reproductive outcomes. We sought to determine the influence of LEA on (i) semen parameters in normozoospermic and abnormal ejaculates; and (ii) the outcomes of sperm-preparation methods in a large number of subfertile men undergoing infertility workups. This retrospective registry-based cohort study analyzed the data of 10,674 ejaculates from 7972 subfertile men, who were then segregated into normozoospermic, oligozoospermic, asthenozoospermic, and oligo-asthenozoospermic cohorts. Variations in semen characteristics and post-wash outcomes were studied between four LEA intervals across 0-15 days. An age-adjusted analysis of covariance (ANCOVA) model linked significant increases in ejaculate volume, sperm concentration (except in the oligozoospermic cohort), and total sperm count to an increased LEA (p<0.05). LEA was negatively associated with motility (except in the asthenozoospermic cohort) and vitality (p<0.05). Large-headed spermatozoa were less common with an increased LEA only in the oligo-asthenozoospermic cohort (p<0.05). In the normozoospermic cohort, a longer LEA led to fewer spermatozoa with amorphous heads but more spermatozoa with tapered heads and cytoplasmic droplets (p<0.05). LEA extension resulted in greater sperm DNA fragmentation in the abnormal cohort (p<0.01). The post-wash sperm concentration and total motile sperm count were significantly improved with a longer LEA in the normozoospermic cohort (p<0.05). Considering the findings in this study and existing literature, a generalized recommendation for long LEA has no clinical value. The LEA should be individualized based on the ejaculate profile and the need for specific clinical intervention.

Relativistic description of the semileptonic decays of bottom mesons

The form factors of the semileptonic $B$, $B_s$ and $B_c$ meson decays are calculated in the framework of the relativistic quark model based on the quasipotential approach in QCD. They are expressed through the overlap integrals of the meson wave function. All relativistic effects are consistently taken into account. The momentum transfer $q^2$ behavior of form factors is determined in the whole accessible kinematical range. We do not use any extrapolations, heavy quark $1/m_Q$ expansion or model assumptions about the shape of form factors. Convenient analytic expressions of the form factors are given, which very accurately reproduce the numerical results of our calculation. On the basis of these form factors and helicity formalism, the differential and total branching fractions of various semileptonic decays of bottom meson are calculated. The mean values of the forward-backward asymmetry $\langle A_{FB}\rangle$, lepton-side convexity parameter $\langle C^\ell_{F}\rangle$, longitudinal $\langle P^\ell_{L}\rangle$ and transverse $\langle P^\ell_{T}\rangle$ polarization of the charged lepton, and the longitudinal polarization fraction $\langle F_{L}\rangle$ for final-state vector meson are also evaluated. We present a detailed comparison of the obtained predictions with the calculations based on the covariant light-front quark model and confront them to available lattice QCD and experimental data. It is found that although both models predict close values of the total branching fractions, the differential distributions and forward-backward asymmetry and polarization parameters differ significantly, especially for the heavy-to-light semileptonic decays. We identify observables which measurement can help to discriminate between models.