Provides automated visual inference of residual plots using computer vision models, facilitating diagnostic checks for classical normal linear regression models.

When many possible multiplier method estimates of a target population are available, a weighted sum of estimates from each back-calculated path can be achieved with this package.  Variance-minimizing weights are used and with any admissible tree-structured data.  The methodological basis used to create this package can be found in Flynn (2023) <http://hdl.handle.net/2429/86174>.

Probability surveys often use auxiliary continuous data from administrative records, but the utility of this data is diminished when it is discretized for confidentiality. We provide a set of survey estimators to make full use of information from the discretized variables. See Williams, S.Z., Zou, J., Liu, Y., Si, Y., Galea, S. and Chen, Q. (2024), Improving Survey Inference Using Administrative Records Without Releasing Individual-Level Continuous Data. Statistics in Medicine, 43: 5803-5813. <doi:10.1002/sim.10270> for details.

Provides tools for assessing and selecting auxiliary variables using LASSO. 
    The package includes functions for variable selection and diagnostics, facilitating 
    survey calibration analysis with emphasis on robust auxiliary vector selection. For 
    more details see Tibshirani (1996) <doi:10.1111/j.2517-6161.1996.tb02080.x> and 
    Caughrey and Hartman (2017) <doi:10.2139/ssrn.3494436>.

Bindings to 'FFmpeg' <http://www.ffmpeg.org/> AV library for working with 
    audio and video in R. Generates high quality video from images or R graphics with 
    custom audio. Also offers high performance tools for reading raw audio, creating
    'spectrograms', and converting between countless audio / video formats. This package 
    interfaces directly to the C API and does not require any command line utilities.

Converts legacy microscopy video formats (H.264/H.265, AVI/MJPEG,
    TIFF stacks) to the modern 'AV1' codec with minimal quality loss. Typical
    use cases include compressing large TIFF stacks from confocal microscopy and
    time-lapse experiments from hundreds of gigabytes to manageable sizes,
    re-encoding MP4 files exported from 'CellProfiler', 'ImageJ'/'Fiji', and
    microscope software with approximately 2x better compression at the same
    visual quality, and converting legacy AVI (MJPEG) and H.265 recordings to a
    single patent-free format suited for long-term archival. Automatically selects
    the best available backend: GPU hardware acceleration via 'Vulkan'
    'VK_KHR_VIDEO_ENCODE_AV1' or 'VAAPI' (tested on AMD RDNA4; bundled headers,
    builds with any 'Vulkan' SDK >= 1.3.275), with automatic fallback to CPU
    encoding through 'FFmpeg' and 'SVT-AV1'. User controls quality via a single
    CRF parameter; each backend adapts automatically (CPU and Vulkan use CRF
    directly, VAAPI targets 55 percent of input bitrate). TIFF stacks use
    near-lossless CRF 5 by default, with optional proportional scaling via
    tiff_scale (multiplier or bounding box, aspect ratio always preserved).
    Small frames are automatically scaled up to meet hardware encoder minimums.
    Audio tracks are preserved automatically. Provides a simple R API for batch
    conversion of entire experiment folders.